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1. June 2014 Volume 8 Article 68 10 Hayworth et al Imaging ATUM ultrathin section libraries NSF Aligned section overview stack 2637 sections across these 16 wafers WAFER 1 WAFER 4 WAFER 7 WAFER 8 WAFER 13 WAFER 14 WAFER 15 WAFER 16 FIGURE 5 Example of a 2637 section UTSL of mouse cerebellum tissue spanning 16 wafers An optical image of each wafer was taken and used as the basis of automapping all sections A Optical image of wafer 8 right filtered optical image with automapped positions of all sections labeled left B Graphical depiction representing the stack of 2637 overview section images acquired during the mapping phase C All 16 automapped wafers in this UTSL of its section overview display Figure 7 allowing the user to scroll through the entire stack of section overviews and graphi cally check placement of the montage tiles across all sections prior to the start of a long imaging run The pixel size Tile FOV Tile width and pixel dwell time must be set to achieve the necessary balance between image scan ning time and image quality Using high contrast staining and the in lens secondary electron detector we were able to obtain images with acceptable noise levels using the maximum scan speed of our microscopes 50 100 ns however these results depend heavily on the tissue preparation and imaging confi
2. Because this tissue is mounted on silicon wafers and imaged with an SEM it is relatively easy to image store and reimage the tissue It is possible therefore to treat ATUM cut samples as an UTSL to be sampled on demand For some experiments large target areas might be imaged once at high resolution Other experiments might involve various small high resolution volumes being fit onto a low resolution map of the total tissue volume The experimental flexibility gained by the UTSL depends critically on developing the means to allow easy navigation within the digital volume This section Imaging strategy and workflow contains an outline of the intent of the low and high resolution imag ing steps The following section Implementation WaferMapper contains a detailed description of the WaferMapper implemen tation Graphical depictions of some of the key concepts UTSL wafer fiducial section overview image aligned stack of overview images target point can be found in Figure 2A LOW RESOLUTION MAPPING The first step in generating a UTSL is mapping the positions of each of the sections on all the silicon wafers The low resolution mapping step can be accomplished using either an optical image or an EM image montage of the entire silicon wafer Sections are identified automatically and then any instances of unlabeled sec tions or debris labeled as sections are corrected manually This Frontiers in Neural Circuits www frontiersin or
3. Once the stage rotation and translation have been adjusted within approximately a mil limeter of the mapped position the user can then run Do all steps for Stage Correction The microscope will then automati cally drive to the fiducial positions take new images and compare Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 11 Hayworth et al Imaging ATUM ultrathin section libraries jil ale fe gre Anca rae H e Ea ea Cara Jejeje a je ye Ie ejeje lel ge Wt i hee At ie ES Ed 1 IES F jte jeje E P ot Gall eal ea Eiri tjelejele p ele Lele 2 f C EAE H Ei Ae Slee Eje j l Aligned section overview stack 1025 sections across these 11 wafers Cc ale gt tje elie elele jbl vile ARARE elele elaela eae stele bail le aeeti elejt AHGORHNE ejeje e fal tleltlelele ltlelelalele tlele bees he lelelelelele Sl tlelele tale tltle ARRE ali selale alt A BA RIEA ARI afefe alelele Y jad Pii ka ba KACA ka sielet lele tjeje alefele PS Boal ball dl a ioe i tjtjejejt See SISIR altlel lelel peleitlelel tlele AESA DARA A A R A alee slelelelelele HRR RGBA iets l WAFER 8 WAFER 9 WAFER 10 afe ele addr jele a e ele AE Ea tleje ef efelelel AG elejei fe wed Sela x Shelf ele elelt ra baie eo tlelelel ale elele led ol ala ea ele ttle elalt lelel ral hale Pi elelelel ale elelel leh Aa viet tle ele t tlelelt pl be
4. imaging can be intelligently targeted and automatically executed In addition WaferMapper checks its own work making sure that it has successfully navigated to the correct position in the tissue and that the images are of acceptable quality Using this software we have been able to collect image volumes from a wide range of ATUM collected tissue libraries including a mouse cortex UTSL a mouse cerebellum UTSL a mouse thalamus UTSL and a larval zebrafish UTSL These 3D image volumes ranged in size from about 1 to 100 terabytes of image data and required the imaging of many thousands of ultrathin sections SAMPLE PREPARATION TISSUE PROCESSING All experiments were performed according to the guidelines of the Harvard Animal Care and Use Committee The tissue samples for ATUM are standard EM blocks preserved using aldehydes stained with osmium tetroxide and embedded in a hard resin Hayat 2000 For large volumes to be imaged quickly good contrast is essential We often use a combination of the R OTO technique for enhancing osmium staining en bloc and lead citrate post sec tion staining Tapia et al 2012 It is important to note that by thickening and darkening membranes this technique can make synapses more difficult to identify in single sections A great deal of this ambiguity is resolved when a synapse is reconstructed in its 3D context There are also a number of staining techniques that can be used to enhance synaptic labeli
5. this process Acquiring a full wafer image An image of the entire surface of the wafer is acquired before mapping of sections begins This image can be generated opti cally or using an electron microscope The benefit of generating the image in the electron microscope is that contrast will be based on electron scattering i e metalized tissue will stand out from the background However full wafer imaging is time consuming Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 7 Hayworth et al Imaging ATUM ultrathin section libraries 20 min on the Merlin and 60 min on the Sigma given that the limited field of view of an electron microscope necessitates acquiring many individual montage tiles We have often found however that even images of the wafer rapidly taken with an opti cal camera while the wafer is being lit indirectly via a diffuse white background are of sufficient quality to serve as a full wafer image so long as all of the ultrathin sections and fiducials are visible in the image Figure 4A The regularity and resolution of the full wafer image will determine how accurately the next stage of mapping overview image acquisition can be targeted We typi cally acquire overview images with a field of view approximately a millimeter larger than the tissue section which corresponds to about a half millimeter of fault tolerance in the full wafer image If WaferMapper already has
6. Acquire section overviews With fiducials mapped sections identified and the stage cali brated WaferMapper has all the information it requires to begin acquiring an overview image of every section on the wafer When the user selects Map Wafer Operations gt Acquire Section Overview Images WaferMapper drives the stage to the first sec tion and begins acquiring images using the user defined settings for this UTSL The default setting is to acquire 3 mm wide images with pixel sizes slightly smaller than 1 ym These settings can be Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 9 Hayworth et al Imaging ATUM ultrathin section libraries changed according to the size of the target sample the accuracy of the section targeting and the desired precision of the 3D map of the UTSL Depending on the number of sections and the imaging parameters the process of acquiring section overviews typically takes 30 min 3 h per wafer depending on the number of sections and the desired overview image quality Repeat for all wafers This mapping procedure is repeated for every wafer in the UTSL Figure 5 shows an example of a fully mapped UTSL consisting of 2637 sections of mouse cerebellum tissue spanning 16 wafers The mapping procedure for this UTSL was based on optical cam era images of each wafer Figure 6 shows an example of a fully mapped UTSL consisting of 1025 sections of mouse co
7. Align section overviews User choose target pointin overview stack Create list of locally aligned target points with IBSC template images cropped from overview images SEM User graphically define montage on section overview and verify placement across 3D stack _ Load a wafer into SEM and perform fiducial based auto reload Load saved target point and montage parameters m e e eee eee ee ee eee eee ee ee ee o More wafers Raw image data ready for offline stitching and alignment Definition Phase and a High Resolution Montage Imaging Phase IBSC Imaged Based Stage Correction see section Starting high resolution image acquisition the defined high resolution volume data Each of these phases is described in detail below SEM WAFER MAPPING PHASE The goal of the SEM Wafer Mapping Phase is to produce a set of images and metadata covering all wafers and all sections in a UTSL This collection of images and metadata e g stage coordinates of all section overview images and fiducial images pixel to stage calibration scaling factor pixel size dwell time etc allows reloading of wafers and automatic movements of the stage to preselected target points within each section Because a UTSL may consist of tens or hundreds of wafers and many thousands of sections we have tried to automate the majority of the steps in
8. C Hildebrand and Jeff W Lichtman 1 Howard Hughes Medical Institute Ashburn VA USA Department of Molecular and Cell Biology Harvard University Cambridge MA USA Edited by Benjamin R Arenkiel Baylor College of Medicine USA Reviewed by Julian Budd University of Sussex UK Richard J Weinberg University of North Carolina USA Correspondence Kenneth J Hayworth Howard Hughes Medical Institute Janelia Farm Research Campus 19700 Helix Dr Ashburn VA 20147 USA e mail hayworthk janelia hhmi org Josh L Morgan Department of Molecular and Cell Biology Harvard University 52 Oxford St The automated tape collecting ultramicrotome ATUM makes it possible to collect large numbers of ultrathin sections quickly the equivalent of a petabyte of high resolution images each day However even high throughput image acquisition strategies generate images far more slowly at present 1 terabyte per day We therefore developed WaferMapper a software package that takes a multi resolution approach to mapping and imaging select regions within a library of ultrathin sections This automated method selects and directs imaging of corresponding regions within each section of an ultrathin section library UTSL that may contain many thousands of sections Using WaferMapper it is possible to map thousands of tissue sections at low resolution and target multiple points of interest for high resolution imaging based on anatomical la
9. a Target and Montage Definition Phase in which WaferMapper usually being run on a non acquisition computer is used to align all section overviews and is used to graphically define a subregion for high resolution montage imaging The final phase is the High Resolution Montage Imaging Phase in which WaferMapper automates the SEM operations necessary to acquire Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 6 Hayworth et al Imaging ATUM ultrathin section libraries ue image of wafer to stage Acquire full wafer SEM montage ee Acquire example section image 7 Automap all sections gt a A d 1 1 Perform pixel to stage i calibration i 1 1 1 L 1 q q od Move stage to target point using reload correction and local alignment correction FIGURE 3 Flow chart showing all key steps in the creation and imaging of a UTSL using WaferMapper The process is broken into three phases an SEM Wafer Mapping Phase a Target and Montage Prepare all wafers I I I L I I L I I I Load a wafer into L I I L 1 L L L L I High Resolution Montage Imaging Phas Execute autofocus strategy i Acquire montage tile i i images Check focus of each tile and perform automatic retakes if necessary More sections on this wafer Target and Montage Definition Phase _ _
10. access to an optical image of a loaded wafer the user can navigate to Map Wafer Operations gt Acquire Full Wafer Montage and select the option to load that camera acquired full wafer image The full wafer image must then be mapped into the microscope s stage space by selecting three or four fiducial points on the wafer s image and manually driving the stage to the corresponding locations To create a new wafer image within the SEM the user can first select Map Wafer Operations gt Wafer Parameters to define the image resolution and dwell time of the full wafer image The user then navigates to Map Wafer Operations gt Acquire Full Wafer Montage defines the edges of the wafer image and begins montaged acquisition Once a full wafer image has been mapped onto stage space or acquired within the SEM the wafer image can be used for naviga tion The user can select Map Wafer Operations gt Free View and then click on any point in the wafer image to drive the stage to the corresponding location Acquire images of wafer fiducial marks At the core of a mapped UTSL is a set of related coordinate sys tems which allows every point in the aligned stack of section overview images to be mapped back to a particular position of the SEM stage Since there is typically a significant offset intro duced when reloading a wafer into the SEM we also acquire a set of images of fiducial marks that are permane
11. alignment procedure that compares neighboring sections but the template matching has the advantage of not accumulating drift and being robust to single problem sections in the stack The automated alignment of each wafer usually takes 10 30 min using 3 2 GHz processors on a standard desktop computer Any mistakes in the alignment can be corrected using Section Overview Processing gt Check and Correct Alignment GUI which calls up an easy to use GUI in which alignments can be quickly reviewed and corrected by simple mouse drags It is not necessary at this point that the resulting alignment is perfect The alignment only needs to be good enough that when an imag ing target point is chosen on one section overview a second stage of target point alignment described below can access the appropriate region of each section overview By following the above procedure a small UTSL can be mapped in several hours A larger dataset consisting of 10 000 sections might take closer to 1 weeks working 8h per day The end product of the mapping process is a set of full wafer images that can be used to navigate around each wafer and a low resolu tion 3D image volume of the tissue sections that can be used to direct high resolution image capture Target point setup The first step of defining a target point for high resolution imag ing is to choose an XY position from within a section overview image This XY position the tar
12. by a full wafer SEM montage left and for an example wafer whose whole wafer image was obtained by an optical camera while the wafer was lit indirectly via a diffuse white background right The Map Wafer Operations gt Threshold image command calls up a new GUI see Figure 4B which is used to set upper and lower gray scale thresholds to convert both the full wafer image and the example section image into binary masks Next the user selects Map Wafer Operations gt Auto Map All Sections to open up the automap GUI see Figure 4C Within this GUI the example section binary mask is used as a convolution kernel and convolved at multiple rotations across the full wafer binary mask The result is a heat map image whose brightest points correspond to high correlations between the wafer image and the example section image Bright points in the heat map image correspond to locations on the wafer image that resemble the example section The user selects a threshold for heat map image and the centroids of image patches that pass threshold consti tute the section locations see Figure 4D With mouse clicks and zoom operations the user can add or remove section positions to correct any mistakes made by the automatic section finding On most wafers there will be a few additions and subtractions to the section list Once all of the sections are marked the sections are automatically assigned number labels according to their p
13. for very large volume reconstruc tions Gay and Anderson 1954 Harris et al 2006 With the introduction of high performance field emission scan ning electron microscopy SEM Joy 1991 Bogner et al 2007 high quality images can be acquired from the sur face of ultrathin sections thereby removing the need to mount sections on an electron transmissive substrate Several new imaging strategies have emerged to take advantage of EM surface imaging to facilitate the production of large EM image volumes One strategy that is based on SEM surface imaging is to image the surface of a plastic embedded block of brain tissue that is mounted directly inside the SEM Tens of nanometers of the block s top surface are then removed by either a microtome in the serial blockface EM SBEM approach or a focused ion beam FIB in the FIB SEM approach to expose a new surface for imag ing This procedure can be repeated many thousands of times to produce a volume EM image set Denk and Horstmann 2004 Knott et al 2008 A second strategy which we adopt in this paper takes advan tage of the surface imaging capabilities of SEM by mounting ultrathin sections on a much more stable substrate than can be used in TEM In the recently invented Automatic Tape collecting UltraMicrotome SEM ATUM SEM process Schalek et al 2011 the ultrathin sections cut by a commercial ultra microtome are immediately and automatically collected from the knife s wat
14. of the electron beam Our experience is that the optimal stigmation changes during an imaging period as the focus depth and microscope conditions change Acquiring a dataset with consistent image quality therefore requires periodic automated focusing and stigmation We find that when we apply the focus algorithms currently available on the Zeiss Sigma and Merlin our focus quality is unacceptable about 5 of the time Therefore high resolution images undergo an automatic quality check which can trigger a corrective focus and stigmation followed by re imaging Because focus and stigmation can take as long as imaging time and fail ure rates can vary with tissue and imaging conditions a variety of focusing strategies are made available described below When the high resolution imaging of a section is completed the digital data is automatically moved from a local data buffer to long term network storage If high resolution imaging is interrupted at any point no data is lost The wafer can be removed from the microscope for stor age and then reloaded when convenient Because this procedure exposes the wafer to air and can affect the microscope cham ber and column conditions there may be a delay of an hour or so before imaging conditions are ideal We have been able to return to a wafer after years of bench top storage for reimaging However it is likely that storing a UTSL for many years without degradation will require placing tissue section
15. volume biological tissue using automated tape collection ultramicro tomy and scanning electron microscopy Microsc Microanal 17 966 967 doi 10 1017 S1431927611005708 Schindelin J Arganda Carreras I Frise E Kaynig V Longair M Pietzsch T et al and Cardona A 2012 Fiji an open source platform for biological image analysis Nat Methods 9 676 682 doi 10 1038 nmeth 2019 Tapia J C Kasthuri N Hayworth K J Schalek R Lichtman J W Smith S J and Buchanan J 2012 High contrast en bloc staining of neuronal tissue for field emission scanning electron microscopy Nat Protoc 7 193 206 doi 10 1038 nprot 2011 439 Conflict of Interest Statement Harvard University has applied for patents covering some aspects of the ATUM SEM process The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest Received 10 April 2014 accepted 05 June 2014 published online 27 June 2014 Citation Hayworth KJ Morgan JL Schalek R Berger DR Hildebrand DGC and Lichtman JW 2014 Imaging ATUM ultrathin section libraries with WaferMapper a multi scale approach to EM reconstruction of neural circuits Front Neural Circuits 8 68 doi 10 3389 fncir 2014 00068 This article was submitted to the journal Frontiers in Neural Circuits Copyright 2014 Hayworth Morgan Schalek Berger Hildebrand and Lichtman Th
16. ware in order to precisely target automated imaging of a small montage volume within the much larger volume of the full UTSL Below we describe the mapping imaging and data set acquired from one test of WaferMapper on the mouse cerebel lum UTSL shown in Figure 5 Table 1 provides actual average data acquisition times and rates for the various steps in the map ping and imaging process These times were recorded during a separate multi month imaging project using the WaferMapper software Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 14 Hayworth et al Imaging ATUM ultrathin section libraries FIGURE 9 Cerebellum UTSL example data A Image of WaferMapper GUI showing a graphically defined 3 x 5 tile montage targeted near the surface of a cerebellar folium Zoom overlays show high resolution images of that region B Montage images of three successive ultrathin sections in this AA APC Aanb VTU tan Draven Raped ma Tonge story o To Target Point With I foc Current Zoom Param Reset Zoom to Full Weg Aayega Omate 20 12 cerebellum UTSL acquired automatically by WaferMapper scale bar 100 um Red arrow shows location of corresponding high resolution images shown in C C Cut outs of high resolution data imaged at 10 MPS and aligned in FIJI scale bar 1 um Asterisks mark position of two synapses CEREBELLUM The cerebellum of an adult mouse was cut i
17. 3 x 3 pixel image kernels from a newly acquired image Figure 8A These samples are then fit into a 200 x 200 by 9 image volume To find a quality value for each grid point we find the rela tive contrast of different patterns within the 3 x 3 pixel kernel One set of patterns finds the difference in the average intensities of adjacent lines of pixels two horizontal comparisons and two vertical comparisons The other set of patterns compares the dif ference in the average intensities between groups of interleaved pixels Figure 8B A well focused SEM image of cell membranes will tend to produce relatively more contrast in the adjacent lines Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 12 Hayworth et al Imaging ATUM ultrathin section libraries Operations Target Pont Setup Montage Setup ML Generate positions from Stage Migs UMY Programs Quick Manual Targeting 99 Stage Play gt gt Stop ltt GoTo Target Point ca Tower Pore wensese ad 14 Section Label Water for tis section ae E 4 fs be ae f FIGURE 7 Examples of graphically defining an imaging target and montage A Image shows the WaferMapper GUI being used to graphically define a 3 x 3 tile montage red boxes covering just the brain region in a larval zebrafish UTSL B Image shows WaferMapper used to graphically define a 3 x 7 tile mo
18. M However these challenges can be overcome and even turned into advantages if software is available to map a tissue library prior to high resolution imag ing With WaferMapper we were able to target the acquisition of large volumes of high resolution images from tissue libraries consisting of many thousands of ultrathin sections We are hope ful that this software will continue to develop within an open source community as it is adapted to new experiments and imag ing systems More generally we believe a multi scale mapping and imaging approach is key to taking advantage of the large number of ultrathin sections that can now be generated using ATUM ACKNOWLEDGMENTS We would like to thank Juan Carlos Tapia and Dan Bumbarger for providing some of the tissue used in the example images This work was supported by NIH NINDS High Resolution Connectomics of Mammalian Neural Circuits TRO1 1R01NS076467 01 and NIH Imprinting a connec tome developmental circuit approach to mental illness Conte 1P50MH094271 01 NIH 5T32MH20017 NIH 5T32HL007901 The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health REFERENCES Bogner A Jouneau P H Thollet G Basset D and Gauthier C 2007 A history of scanning electron microscopy developments towards wet STEM imaging Micron 38 390 401 doi 10 1016 j micron 2006 06 008 Denk W and Horstman
19. SEMs Carl Zeiss Microscopy LLC Oberkochen Germany fitted with Fibics scan generators Fibics Inc Ottawa Ca All results presented here were imaged with one of these microscopes The Fibics scan generator allowed for images to be acquired with pixel dimensions up to 32 by 32k Both of these microscopes have multiple detec tors that include an outside the lens secondary electron detector a below the lens backscatter detector and an in lens secondary electron detector We use the in lens secondary electron detector for high speed imaging because this detector s response speed was sufficient to keep up with high scan rates 10 MPS in the case of the Sigma and 20 MPS in the case of the Merlin When imaged with this detector our samples yielded the best signal using 1 7 3 5 keV and therefore required collection on an ATUM tape hav ing conductive coating rather than thin film carbon coating the sections after collection We also found that the depth of field mode with extended depth of focus available with the Merlin is helpful for acquiring large fields of view of potentially uneven surfaces Both microscope types were also fitted with an Evactron plasma generator XEI Scientific Redwood City CA to clean and etch surface material before imaging tape affixed to wafers IMAGING STRATEGY AND WORKFLOW A consequence of automated sectioning is that far more tissue can be cut than can currently be imaged at the highest EM resolu tion
20. SVN server We encourage other users of the WaferMapper software to test code and to add to the repository as new solutions are developed STITCHING AND ALIGNMENT Small EM volumes lt 1 terabyte can be aligned on a power ful desktop computer using publicly available alignment software such as the registration plugins for Fiji Schindelin et al 2012 However the stitching and alignment of high resolution images becomes increasingly difficult as data sets become larger The computational power required to manipulate and process ter abytes of images requires hardware that is not standard in most labs and while most steps in alignment are amenable to paral lelization running these steps in parallel often requires changes in code and expertise in managing clusters Because of these prob lems aligning multi terabyte datasets is currently being done by only a few groups However the recent production of many multi terabyte EM volumes has spurred efforts to scale up alignment tools to make it easier for the broader research community to turn hundreds of terabytes of EM images into usable 3D tissue maps THE PROMISE OF ULTRATHIN SECTION LIBRARIES FOR COLLABORATIVE CONNECTOMICS A major goal of the integration of automated tape collection and automated imaging of sections is to make volume EM easy enough to bea standard technique that many labs can use to study biological samples that are tens or hundreds of micrometers wide However we als
21. This overview image volume can be used to plan efficient targeted high resolution imaging volumes encompassing only those regions crucial to the biological study at hand Additional high resolution imaging forays on the same sectioned material can be conducted at multiple later times if desired The importance of this ability becomes apparent when one considers the time and storage requirements involved in imag ing 3D volumes at nanometer resolutions For example consider a 0 5 x 2 5 x 3mm block of mouse brain trimmed to encom pass regions of the lateral geniculate nucleus LGN and pri mary visual cortex V1 along with intact axonal projections connecting the two MacLean et al 2006 On the ATUM such a visual thalamocortical slice block could potentially be reduced to a tape of 17 000 x 30nm thick sections collected Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 2 Hayworth et al Imaging ATUM ultrathin section libraries with just a few days of sectioning If imaged in total with a typical 5 nm in plane resolution this volume would require stor age of 5 petabytes of image data 17 000 sections each montage imaged with 500 000 x 600 000 pixels Worse still if imaged at a standard rate of about 10 megapixels per second a single microscope would require over 15 years to image the volume seemingly putting such a study out of reach today However the actual connected regio
22. di Slelelelel ele elelel le Cas ibaa elat tle vlelel lele t sie ae alelelele a e elelelole Pelee ltlele x elele elejti eje t Hide ejt ejejejelg jele noana PORRA elel i tle alal l lele a2 at elelelelel lele ejeje ilei Ele la lflale xX eltle ejet jeet FA I ejt elelelele ele elelel lel leleleltiele KSE ele Plele ey le elf eleleiel e jejej le Car PSP a Pgs iali HARSA flee ee ejeje elellelelelelelelele ee ielele eelelen e REE Saige Atenas Gann N Maan WAFER 1 WAFER 12 WAFER 13 WAFER 14 WAFER 15 WAFER 16 FIGURE 6 Example of a 1025 section UTSL of mouse cortex image with automapped positions of all sections labeled left B tissue spanning 11 wafers A full wafer SEM montage image of Graphical depiction representing the stack of 1025 overview section each wafer was taken and used as the basis of automapping all images acquired during the mapping phase C All 11 automapped sections A Full wafer SEM montage of wafer 6 right same wafers in this UTSL these images with the original images of the fiducials This com parison is used to find a coordinate transformation that will be used to translate between stage space and wafer map space for the remainder of the imaging session This ability to automatically register a reloaded wafer is also crucial when it is necessary to retake images when imaging a new region and when sharing a UTSL between different laboratories Once reloaded a
23. ection erg aipe orget Orta 28 12 tissue section on the wafer level overview display is marked by a red cross along with its section number In the section overview display a red cross designates the target point for high resolution imaging In this case the red cross is overlaid by a smaller blue cross designating where autofocuses should occur which in general can be offset from the target point The yellow box in the section overview display denotes the field of view used for local target point alignment see section Target point setup The red boxes in the section overview display are the high resolution montage tile positions defined in the montage parameters see section Montage parameters procedure marks the position of each section For the micro scope to consistently find the mapped section positions reference points fiducials are imaged on each wafer Figure 2A Any time a mapped wafer is loaded into the SEM the fiducial points are re imaged and compared to the original fiducial images to deter mine the correction factor required to translate the wafer map coordinate system onto the new wafer position The second step in creating a UTSL requires obtaining a more detailed low resolution image of each section but not the whole wafer For this imaging phase the microscope automatically uses the map of section positions obtained for each wafer see above to drive the microscope stage to each section on a
24. el kernels is extracted from an SEM image B Structured top and unstructured bottom contrast patterns are compared to obtain a quality value for each 3 x 3 pixel kernel C Stage stitched montage of images displayed with quality values in green passing and red below threshold procedure can take significantly longer than the acquisition of a single tile Therefore a variety of strategies are offered in WaferMapper for increasing the efficiency of high throughput data collection In many cases a single autofocus before each montage will be sufficient to produce acceptable image quality For large montages a three by three grid of focus points can be acquired and then fit to a plane that predicts the optimal focus point for each tile of the large montage Alternatively tiles can be pooled and a central focus point acquired before a two by two box of tiles is acquired In a typical example we might choose to focus stig focus once per section as long as image quality stays above threshold When the microscope starts a new section it will first drive to a pre defined central focus point within the montage The microscope then takes a quick image approximately the size of an image tile and drives to the region within the image with the highest con trast In this way WaferMapper avoids autofocusing on regions such as the interior of blood vessels which provide no useful information to the focus algorithm The microscope then
25. er boat onto the surface of a partially submerged con veyor belt made of sturdy plastic tape Figure 1 SEM imaging of the series of sections collected on the tape produces a dataset of micrographs which renders individual planes through a 3D tis sue volume This tape collection allows thousands of ultrathin sections to be collected in an automatic way Because of the unin terrupted flow of tissue onto the relatively wide conveyor belt the sections obtained can be thinner larger in area several square Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 1 Hayworth et al Imaging ATUM ultrathin section libraries FIGURE 1 ATUM SEM process A Picture of ATUM tape collection device installed on a commercial ultramicrotome housed in an environmental control chamber B Side view of ATUM C D Sequential video images of section collection E CAD rendering of ATUM showing path collected sections take from the knife boat to the final take up reel F CAD zoom in on knife boat showing collection process G Picture of unraveled tissue tape on take up reel containing a series of ultrathin sections Each dark rectangle is a section H Picture of a 100mm diameter silicon wafer with 10 tissue tape strips adhered to it There are a total of 162 ultrathin sections on this one wafer I Picture of 20 wafers all filled with tape strips from a single ATUM run consisting of over 15m of tiss
26. es and image conditions When starting image acquisition the user will also be asked whether or not WaferMapper should use IBSC The accuracy of targeting we were able to achieve using wafer fiducials only was usually limited to about 15 um We found that we could sig nificantly improve this accuracy using IBSC When this option is selected WaferMaper acquires a quick image every time it drives to a new section This image is processed using a difference of Gaussians filter to enhance features on the scale of cell bodies This section s aligned subregion target image cutout of the sec tion overview image after local alignment during the Target Point Setup step see section Target point setup is likewise filtered and compared with the newly acquired image using cross correlation If the stage movement was completely accurate then the two images should match exactly If they do not then WaferMapper uses the offset obtained from the cross correlation to adjust the stage position and then checks its work with a second image The accuracy with which this second image matches the section overview target is also recorded within the log file EXAMPLE DATA Data sets have been acquired using WaferMapper that range in size from 1 to 100 terabytes Figures 9 10 show some exam ple images from WaferMapper runs of a mouse cerebellum UTSL and a mouse cortex UTSL These figures illustrate the range of scales which must be spanned by the mapping soft
27. essary to allow quick and easy random access imaging of any point in the volume These mapping steps are performed through our custom SEM automation software WaferMapper Our vision is that a researcher using such an UTSL and WaferMapper should be able to quickly browse through the entire tissue volume at low resolution identify salient anatomical fea tures and then graphically specify a subvolume for automated imaging The WaferMapper software then instructs which wafers to load into the SEM leaving the software to automate all subse quent imaging operations In order to take full advantage of a large tissue library the mapping and imaging software must meet the following criteria Automated imaging The first goal of an automated image acquisition software package is to allow a user to image the corresponding region of tissue on all of the sections in a tis sue library without having to manually direct the microscope to each section Ideally the user should be able to pick a tar get region within the software load a wafer and leave the microscope while the imaging takes place automatically High throughput To reconstruct large regions of tissue at high resolution images must be acquired quickly Scan speeds within a single image currently range from about 0 5 to 20 million pixels per second MPS using the commercially avail able SEMs and detectors described in this paper This large range of imaging speeds reflects the wide
28. etup menu the user can choose to have the quality check performed at sev eral points in the image acquisition process First a quality check can be performed after each autofocus to determine if the cor rect working distance has been obtained After each autofocus WaferMapper can take a quick image and perform a quality check If the quality value exceeds the user defined threshold high resolution imaging begins Otherwise the image is refocused Second the user can choose to have a quality check performed after each tile is acquired If the image quality fails to pass a user defined threshold the image is refocused and retaken Finally the quality values of each tile are displayed on the down sampled stage stitched image of the montage Figure 8C Stage stitched images with the quality values displayed on top provide an easy way for the user to monitor the imaging process and to review the performance of the microscope Focusing strategies The best possible image quality will usually be achieved by autofocusing then autostigmating and then autofocusing again focus stig focus before each tile is acquired However this Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 13 Hayworth et al Imaging ATUM ultrathin section libraries FIGURE 8 Structure of quality check procedure A A 200 x 200 array of 3 x 3 pix
29. ex UTSL a hippocampal slice UTSL etc Some of these UTSLs may even be designed to include prior functional Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 17 Hayworth et al Imaging ATUM ultrathin section libraries imaging to augment expected connectomics studies This design of UTSLs tailored for wider research interest would be similar to the way some labs today specialize in the creation of trans genic animals designed specifically for wider research use Other labs would then specialize in curating and EM imaging these UTSLs providing perhaps for a fee the highest quality 3D vol ume data on request of research groups This strategy would be similar to the way some groups in the astronomical com munity specialize in the design and construction of the highest quality telescopes whose specifications far outstrip the funds and resources of any single astronomical research group We would like to argue that for truly large scale cellular connectomics the neuroscience community has reached a similar need for pooling of resources and a similar need to create dedicated Connectome Observatories whose high quality large volume EM imaging abilities are designed to be shared by the entire neuroscience community CONCLUSION There are many challenges to imaging ultrathin sections that are absent from technologies that image intact tissue such as con focal imaging SBEM or FIB SE
30. ferMapper interfaces with SEM hardware WaferMapper can be run as a standalone application for steps which do not require SEM con trol A UTSL directory structure stored on a network file sys tem organizes all metadata and images related to a particular library Figure 2C shows the WaferMapper graphical user inter face GUI The GUI is organized around a wafer level overview display and a section overview display The red crosses designate the position of mapped sections When WaferMapper is con nected to the SEM and the currently loaded wafer is displayed the user can quickly move the SEM stage position to any point on the wafer by clicking on the wafer image or to any point in a section by clicking on and zooming in on the section overview display When WaferMapper is run on a computer not connected to the SEM the user can browse through all wafer images and through the entire stack of aligned section overviews to graphically define a target region for high resolution montage imaging Figure 3 is a flowchart showing all key steps in the cre ation and imaging of a UTSL using the WaferMapper software Conceptually the process is broken into three key phases The first is an SEM Wafer Mapping Phase in which the software is used to map out the locations of all sections across all wafers in the library and in which low resolution overview images of all sections are acquired by automation of SEM stage movements and imaging The second is
31. g June 2014 Volume 8 Article 68 4 Hayworth et al Imaging ATUM ultrathin section libraries Tissue Fiducials Sy ATUM Ultrathin Section Library SmartSEM API stage and fsusl lt SEM control Visual Basic API wrappers NS FiBics API imaging Waerttapper Y WaywoatiMasterTSLDeACerebedum_JM_YRIC_JustoO8_ UTSUWGOS FIGURE 2 Overview of WaferMapper terminology SEM system integration and Graphical User Interface GUI A Graphical depiction of some of the key terms described in the text B Block diagram showing how one copy of the WaferMapper program is used to automate SEM imaging while a separate copy is used to handle offline tasks such a browsing the aligned section overviews stack and graphically planning montage imaging volumes A central UTSL Directory structure organizes all metadata and images related to the library C The WaferMapper GUI is organized around a wafer level overview display left and a section overview display right Each n Aligned Stack of Section Overview Image Overview Images Copy of WaferMapper run on FIBICS control computer Copy of WaferMapper run on separate computer UTSL Directory on network file system pueri See Mere Meter YRC ita UTELO Set Orewa Mapes rian recto 4 3 1 GoTo Target Eetun Zoom Parme Section Label So Te Taget Port wan gt g Reset Zoom to Full Generate positions fr Water for this s
32. get Point Setup gt Check and Correct Target Point Alignment GUI The results of each target point alignment are stored in a new Aligned Target List subdirectory in the UTSL contain ing all of the aligned subregion images for use in image based stage correction IBSC described below and a new datafile called AlignedTargetList mat AlignedTargetList mat contains the pixel offsets needed to align each of these cropped subregions These pixel offsets when combined with the pixel to stage cali bration factor determined during the mapping phase will be used in the high resolution imaging phase to quickly position the SEM stage for imaging each section Montage parameters The position dimensions and imaging conditions of each high resolution dataset are defined within Montage Setup gt Set Montage Parameters The central position of each image mon tage is set relative to the aligned target point by defining an X offset Y offset and North Angle The dimensions of the mon tage are set by defining the field of view of each tile Tile FOV and the number of rows and columns of tiles in each montage Additionally the overlap between tiles is defined here For our systems four micrometers of overlap was sufficient to consis tently acquire images without gaps between tiles WaferMapper provides a graphical overlay of the montage tile positions on top Frontiers in Neural Circuits www frontiersin org
33. get point will be used as the ref erence point for targeting high resolution imaging and will serve as the center of a second stage of more precise local alignment of the section overviews The user selects a target point by loading a UTSL and wafer into WaferMapper and selecting Target Point Setup gt Choose Target Point in Aligned Section Overview The user is then prompted to click on a point within the displayed sec tion overview image and can save the target point for later use Unlike the previous steps in the wafer mapping process in which it is expected that a single map is generated for a given UTSL the selection of target points is a branch point where many target points can be defined one for each high resolution subvolume to be imaged Once a target point is selected a new targeted alignment is exe cuted by selecting Target Point Setup gt Generate and Save List of Aligned Target Points For this alignment a relatively small window is extracted from each section overview image Each sub region of the section overview images is aligned to a running average of previously aligned subregions This process takes about 10 min per wafer The goal of this second stage of alignment is to produce a better local section to section registration than can be generated from an alignment of the entire section overview images themselves Once this alignment is completed any mis takes can be corrected using the Tar
34. guration The Fibics scan generator allows image sizes up to 32 x 32k pixels which means 100 um wide images can be acquired at 4 nm per pixel resolution Being able to scan large field of view images at high resolution reduces the impact of tile to tile overhead on image acquisi tion time and generally increases the efficiency of managing large datasets WaferMapper includes the option to take an overview image of the targeted imaging region before the high resolution imaging begins Being able to take advantage of this option requires that the microscope setup that is used to acquire high resolution images is also amenable to large field of view imaging HIGH RESOLUTION MONTAGE IMAGING PHASE Reload Once the section overviews have been acquired the wafer can be removed from the microscope and stored When the wafer is placed in a new SEM or returned to the same one the position of the wafer on the stage will not be exactly the same as when the wafer was mapped To bring the wafer map into register with the new position on the stage the user can follow the steps listed under the Reload Wafer Operations menu The first step is to manually set the coarse offset of the stage The microscope drives to the first fiducial point on the wafer and the user manually rotates and translates the stage to correct for any gross change in position Free view with Offset can then be used to confirm that the new wafer position is roughly correct
35. ing 2 Intel Xeon x5672 3 2 GHz 4 core processors Section overview alignment automatic Manual correction of overview alignment Target point alignment Manual correction of target point alignment 10 30 min wafer 0 20 min wafer 10 30 min wafer 0 20 min wafer High resolution imaging Time per wafer Wafer load into microscope WaferMapper reload procedure Montage setup 5 or 45 min wafer with or without load lock 10 min wafer 5 min wafer Montage time Movement to section Image based stage correction Focus stigmation focus Pixel dwell time Time between tiles with quality check 10s 1 min 2 min 50 3000 ns depending on tissue signal and detector 8s Estimated project breakdown High speed imaging of 10 000 sections using 100 000 x 100 000 pixel montages Raw pixel scan time minimum Montage acquisition time with overhead Total data acquisition time start to finish 57 days 104 days 130 days Asterisks indicate steps that could significantly benefit from further software development Forrest Coleman aligns SURF points over a large number of sec tions as an alternative to cross correlation to improve the targeting of high resolution imaging within UTSLs We find that this solu tion is often more robust than the current implementation of cross correlation This branch of the code and others will be made available through the Google Code
36. is is an open access article distributed under the terms of the Creative Commons Attribution License CC BY The use distribution or reproduction in other forums is permitted provided the original author s or licensor are credited and that the original publication in this journal is cited in accordance with accepted academic practice No use distribution or reproduction is permitted which does not comply with these terms Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 18
37. n H 2004 Serial block face scanning electron microscopy to reconstruct three dimensional tissue nanostructure PLoS Biol 2 e329 doi 10 1371 journal pbio 0020329 Gay H and Anderson T F 1954 Serial sections for electron microscopy Science 120 1071 1073 doi 10 1126 science 120 3130 1071 Harris K Perry E Bourne J Feinberg M Ostroff L and Hurlburt J 2006 Uniform serial sectioning for transmission electron microscopy J Neurosci 26 12101 12103 doi 10 1523 JNEUROSCI 3994 06 2006 Hayat M A 2000 Principles and Techniques of Electron Microscopy Biological Applications Cambridge New York Cambridge University Press Joy D C 1991 The theory and practice of high resolution scanning electron microscopy Ultramicroscopy 37 216 233 doi 10 1016 0304 3991 91 90020 7 Knott G Marchman H Wall D and Lich B 2008 Serial section scanning electron microscopy of adult brain tissue using focused ion beam milling J Neurosci 28 2959 2964 doi 10 1523 JNEUROSCI 3189 07 2008 MacLean J N Fenstermaker V Watson B O and Yuste R 2006 A visual thalamocortical slice Nat Methods 3 129 134 doi 10 1038 nmeth849 Morgan J L and Lichtman J W 2013 Why not connectomics Nat Methods 10 494 500 doi 10 1038 nmeth 2480 Schalek R Kasthuri N Hayworth K Berger D Tapia J Morgan J et al 2011 Development of high throughput high resolution 3D reconstruction of large
38. ndmarks The program can also be used to expand previously imaged regions acquire data under different imaging conditions or re image after additional tissue treatments Keywords connectomics ATUM volume EM scanning electron microscopy ultramicrotome imaging software tape collection serial section electron microscopy Cambridge MA 02138 USA e mail joshmorgan fas harvard edu INTRODUCTION The three dimensional 3D structure of biological tissues can be ascertained at high resolution by cutting plastic embedded tis sue into a series of ultrathin sections imaging those sections with an electron microscope and reconstructing the objects contained therein volume EM Obtaining such volumetric reconstructions is especially useful for analysis of nervous system samples because nerve cells distribute their processes over extended volumes and only with the resolution of electron microscopy EM is it pos sible to identify the network of synaptic connections between all the neurons This dense synaptic connectivity data is criti cal to understanding how nervous systems process information Morgan and Lichtman 2013 Until recently volume EM required manually collecting a series of ultrathin sections onto the nanometers thin plas tic film of a transmission electron microscope TEM grid Because of the thin substrate the process of making serial sections can be painstaking and is subject to tissue loss that poses a serious challenge
39. ng Regrettably most EM protocols were not developed to penetrate volumes that extend for 100 s of microns in depth The lack of uniformity in staining in general can be a significant problem More uniform staining can be achieved by decreasing stain concentration and increas ing incubation time However with any particular sample there Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 3 Hayworth et al Imaging ATUM ultrathin section libraries is a significant risk that the stain will not be acceptable all the way through the volume One of the benefits of generating the low resolution image series with WaferMapper is that the thou sands of sections can be evaluated for tissue quality before the more time consuming high resolution imaging is begun Once high resolution imaging is completed WaferMapper can also be used to reimage ambiguous structures under different imaging conditions or after further post section staining SECTIONING AND SAMPLE PREPARATION ATUM uses a reel to reel conveyor belt to collect sections from the water boat of standard ultramicrotome diamond knives Once sections are cut and float into the water boat they come in contact with the inclined surface of the moving collection tape that juts out of the water Figure 1 Depending on the size of the tissue block 1000 10 000 sections can be collected over a 24h period with no human interaction Once the ATUM sectio
40. ng mosaic resolu tion and other imaging parameters Once these parameters are set each wafer can be loaded onto the microscope stage and imaged automatically High resolution data collection begins with loading a wafer and imaging the fiducials to adjust the wafer s section overview map to register it to the new position of the wafer on the micro scope stage These adjustments are typically in the range of 100s of microns With the montage parameters loaded the microscope now has sufficient information to acquire a series at high reso lution for each loaded wafer Once the high resolution imaging step is initiated the microscope automatically moves the stage to the first section and then moves to the target position The scan rotation based on the stored parameters is initiated so that all the sections are acquired in the same orientation The microscope then automatically adjusts focus and stigmation at the target region Correct focus and stigmation are critical for SEM imaging of tissue sections spread across ATUM tape strips and adhered to silicon wafers The depth of field in typical SEM imaging is small relative to typical wafer and tape mounting variability The beam focus must therefore be adjusted to match the z position of the tissue as the stage moves across millimeters of tissue and centimeters of silicon wafer Generating a high resolution beam spot also depends on stigmators compensating for any aberra tions in the focusing
41. ning and col lection process is started the operator typically leaves the room and can check in on cutting remotely via video Knife water level is maintained automatically by a video feedback mechanism con trolling a digital syringe pump After sectioning about 100 um of tissue the microtome reaches the end of its useful range and has to be manually reset At this time the sample can also be moved to a fresh position on the diamond knife so that knife sharpness does not become a problem In this way large volumes can be sectioned with only a single interruption every several thousand sections For some samples it is possible to collect thousands of sections without tissue loss However many factors such as heterogenetity in the tissue and knife dullness can result in sections breaking or folding as they are being cut For most connectomics applications we are able to tolerate one or two damaged sections per hundred as long as damage is not occurring in sequential sections The tape containing the sections is next cut into strips and mounted on 100 mm diameter silicon wafers which are flat con ductive doped and vacuum safe To adhere the tape to the wafer the surface of the wafer is covered with double sided conduc tive tape Each section needs a path to ground or it will become electrically charged during SEM imaging This grounding can be accomplished by thin film depositing a carbon coating over the entire surface of the wafer with ta
42. ns of the LGN and V1 represent only a tiny fraction of the full slice volume which they span If one could direct high resolution imaging mainly to those regions which are actually connected then the total imaging time could potentially be reduced by a factor of 10x or more One way to efficiently direct such high resolution imaging would be to uti lize an iterative process of first making a low resolution image set of the entire volume and then use several passes of directed medium and high resolution imaging to narrow in on and even tually high resolution image only those parts containing an intact thalamocortical circuit An additional advantage afforded by non destructive ultrathin section collection is that imaging time can be further reduced by dividing up the ATUM tape so that it can be simultaneously imaged in parallel across multiple SEMs This type of parallel multi scale directed access volume EM imaging which is not possible in blockface approaches and extremely difficult when handling individual TEM grids is pos sible given the large tissue volumes and the robustness to re imaging and tissue handling of the ATUM SEM technique In this paper we use the term UltraThin Section Library UTSL to describe a collection of many thousand ATUM collected ultra thin sections which have been securely mounted on wafers for SEM imaging and which have undergone all of the coordinate mapping steps and low resolution overview imaging nec
43. ntage red boxes covering a single worm in a C elegans UTSL Note the ability to selectively designate a subset of montage tiles for imaging Of crucial importance is the St TLD Morta Seu IM Stage Mage Lamy Program Quick Manusi Targeting money Goto Goto Next Save And Goto Next Stage Piay gt gt Stop Sanati ate Edit Text Section Label ball Ltt CoToTmgatPon amezontumen Go Te Target Port Wen BSC Generate positions trom Water hee Bes section software s ability allowing the user to scroll through the entire stack of section overviews to graphically check placement of the imaging montage across all sections prior to the start of any long imaging run The yellow box in the section overview display denotes the field of view used for local target point alignment see section Target point setup The small blue cross denotes the autofocus position to be used which in this case is deliberately offset from the center of the montage pixel patterns than in the interleaved pixel patterns Once a qual ity value is obtained for each grid point a quality value for the entire image is obtained by averaging a small percentage of the best grid points In this way changes in tissue statistics have a rel atively small effect on the quality rating This method can also be used to identify poor quality regions of the tissue or of the imaging field Within WaferMapper s Montage Parameters s
44. ntly placed on the corners of the wafer The stage positions of these fiducial points are used as a reference frame for all other stage posi tions The first step of acquiring overview images is therefore to image the fiducial points on the wafer first at low resolu tion 3m per pixel then at high resolution 0 25 1m per pixel By selecting Map Wafer Operations gt Acquire Low Res Fiducials the user can use the full wafer image to navi gate to fiducial points on the wafer and acquire images of these points These images can then be used any time the wafer is reloaded to map section overview space back onto microscope stage space Automap all sections Once the fiducials have been imaged the next step is to automat ically determine the positions of all sections on the wafer The user selects Map Wafer Operations gt Acquire Example Section Image and either is directed to cut out an example image of a section from the full wafer image if a full wafer optical image is being used or is able to acquire a new example image of a section by SEM if a full wafer SEM montage is being used This example section image is then used as a template which is scanned across the full wafer image at a range of image rotations to pick out the positions of the other sections with sufficient precision to drive section overview imaging This process is displayed in Figure 4 for an example wafer whose whole wafer image was obtained
45. nto several 300 pm thick vibratome sections and stained with osmium tetroxide and uranyl acetate The tissue was embedded in Embed 812 Electron Microscopy Sciences A block containing one of these vibratome sections was trimmed to include a 1 x 3mm wide region of cerebellum The blockface was trimmed so that the leading and trailing edges of each section come to a point This shape helps minimize cutting disruptions caused by the contact of the block face with the diamond knife and the removal of the section from the edge of the diamond knife Eight thousand ultrathin sections were cut at a thickness of 30 nm and collected on carbon coated Kapton tape A subset of this ATUM run s tape containing 2637 sections was cut into strips and mounted on 16 wafers as shown in Figure 5 Mapping The WaferMapper software was used to map these 16 wafers and acquire overview images of each section to generate a low resolu tion 3D map of the tissue Viewing the aligned overview stack in Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 15 Hayworth et al Imaging ATUM ultrathin section libraries FIGURE 10 Progressively higher resolution images through a mouse cortex UTSL mapped and imaged by the WaferMapper software A Single section of the 1025 section mouse cortex UTSL whose wafers are displayed in full in Figure 6 This image is from a screen capture of the WaferMapper program showing the loca
46. o stage conversion factor is Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 8 Hayworth et al Imaging ATUM ultrathin section libraries A Full Wafer SEM Montage Full Wafer Optical Image highpass filter rarer ar a oe ot 0 oe e t t t b g t La b t g bha 3 Sis gt Sie n seed 3 22 gt gt OF 6 Lemania y FIGURE 4 WaferMapper process steps for automatically finding the positions of all sections on a wafer A Acquisition and registration of a full wafer image to the SEM stage using either a full wafer SEM montage left or a full wafer unprocessed optical image right B Thresholding of full wafer image and example section image creating binary masks C Convolution of SEM stage positions of all sections recorded Ready to direct acquisition of section overview images the example section mask over the full wafer image creates a heat map whose hottest points correspond to likely section locations D After the user selects a suitable threshold for the heat map the program marks the locations of all centroids as individual sections and numbers the sections in strips according to the order the tape strips were collected on the ATUM machine obtained and recorded as part of the metadata associated with this wafer
47. o wish to stress the potential of UTSLs to allow a new type of collaborative neuroscience As discussed above the ATUM in a few days of cutting can potentially produce so many ultrathin sections that it might take decades to image them in total at high resolution A typical research publication using ATUM SEM and WaferMapper might end up acquiring high resolution images from only 1 of the total volume of a collected UTSL For example in the visual thalamocortical slice case outlined in the introduction one researcher may end up imaging and sparsely tracing only a finely targeted 300 x 300 x 300m volume in cortical layer IV mapping out the local connectivity of thala mic afferents and interneurons in that area Once this research is published other labs may wish to build upon this connectomics data by performing additional imaging and tracing in neighbor ing regions of the same brain literally starting their tracing work from the very same neurons in this already published study In this way a collaboration of multiple research labs could muster the time and resources necessary to elaborate the connectomes of larger inter regional circuits than any one lab could by working alone In this paradigm some research labs might specialize in pro ducing UTSLs with the highest quality ultrastructure preservation and staining encompassing brain regions that are of interest to many labs for example a visual thalamocortical slice UTSL a barrel cort
48. osition on the collection tape Typically this automap process will find and correctly label gt 95 of sections on a wafer Sections that are not identified automatically usually because they lay close to a high contrast edge or because two sections are too close together can be identified manually and added by the user with a few mouse clicks Pixel to stage calibration To use overview images of sections to direct stage positioning the relationship between pixel size and stage travel must be precisely defined Slight inaccuracies arising from imperfect calibration of the microscope can result in noticeable errors in WaferMapper s ability to target the correct region of tissue To compensate for potential discrepancies between pixel size and stage travel we perform a pixel to stage calibration immediately before the acquisition of the section overview images This process produces a pixel to stage conversion factor which is specific to the partic ular set of imaging conditions used for the overview images The pixel to stage conversion factor is determined by selecting Map Wafer Operations gt Perform Pixel to Stage Calibration The user is then prompted to select an image target The microscope takes an image of the target region using the same settings that will be used to acquire the section overview images moves the stage a defined distance and then takes a new image By comparing the displacement in the images a pixel t
49. pe strips attached typically works well with backscattered electron detection If the tissue will be imaged using voltages that cannot penetrate a carbon coat ing see section Imaging Hardware use of a collection tape that is pre coated with a conductive layer is required The top sur face of the conductive tape can then be connected to ground by using conductive tape or paint along its edges Because this approach also works with backscattered electron detection we are able to first use backscattered imaging to acquire large field of view overview images with minimal field distortion because of high electron voltages and then switch to secondary electron imaging if it is optimal for the smaller field of view high resolution imaging step Once the tape segments are mounted onto silicon wafers we affix fiducial markers Copper Reference Finder TEM grids style H6 from Ted Pella work well to the double sided carbon tape at the corners of the wafers This is critical for the wafer mapping process described in detail below A standard wafer box Figure 1 can hold 25 silicon wafers containing hundreds of sections each resulting in a 10 000 section UTSL that can be stored in a desk drawer IMAGING HARDWARE There are several SEM imaging systems commercially available that could be used for imaging ultrathin section libraries gen erated by ATUM sectioning The software presented here was developed to drive off the shelf Sigma and Merlin
50. per forms a focus stig focus and begins imaging the first section The order in which the tiles are imaged is determined by the proximity of the focus point so that if refocusing is required best advan tage is taken of each focus point Once an image is acquired the quality is evaluated If the tile passes the microscope moves onto the next tile If the tile fails the microscope refocuses and takes the image again At any point in the imaging process a user can review either the images or the quality values being produced by the microscope and assign sections to be retaken This strategy of only focusing once if the quality values stay above threshold works well when image acquisition time is small relative to the time it takes to autofocus and when the majority of tiles can be imaged using a single focus point Starting high resolution image acquisition With the aligned target points loaded and the montage param eters set WaferMapper is ready to acquire images The user selects Montage Setup gt Acquire Montage Stack Main and is prompted to select a target directory This target directory can be anywhere however image writing and quality check work best if the data is saved on a local solid state drive This data can then be managed and transferred through a network connection to a large data server In addition to writing the images in this direc tory a log file is written that records all stage movements image qualiti
51. pew DIGITAL ACCESS TO el SCHOLARSHIP AT HARVARD Imaging ATUM ultrathin section libraries with WaferMapper a multi scale approach to EM reconstruction of neural circuits The Harvard community has made this article openly available Please share how this access benefits you Your story matters Citation Hayworth Kenneth J Josh L Morgan Richard Schalek Daniel R Berger David G C Hildebrand and Jeff W Lichtman 2014 Imaging ATUM ultrathin section libraries with WaferMapper a multi scale approach to EM reconstruction of neural circuits Frontiers in Neural Circuits 8 1 68 doi 10 3389 fncir 2014 00068 http dx doi org 10 3389 fncir 2014 00068 Published Version doi 10 3389 fncir 2014 00068 Accessed December 16 2015 3 22 51 PM EST Citable Link http nrs harvard edu urn 3 HUL InstRepos 12717378 This article was downloaded from Harvard University s DASH repository and is made available under the terms and conditions applicable to Other Posted Material as set forth at http nrs harvard edu urn 3 HUL InstRepos dash current terms of use LAA Terms of Use Article begins on next page frontiers in NEURAL CIRCUITS METHODS ARTICLE published 27 June 2014 doi 10 3389 fncir 2014 00068 Imaging ATUM ultrathin section libraries with WaferMapper a multi scale approach to EM reconstruction of neural circuits Kenneth J Hayworth Josh L Morgan2 Richard Schalek Daniel R Berger David G
52. range of staining techniques used in connectomics studies as well as differences in the efficiency and bandwidth of different types of detectors used under various imaging conditions Ideally the acquisi tion overhead time spent between image scanning should be less than the actual image acquisition time Eliminating human involvement in the image acquisition procedure is an important part of reducing overhead In addition however automated steps such as stage movements focusing and image retakes also need to be accomplished quickly so as not to slow down the throughput We provide a table breaking down actual data acquisition times for key WaferMapper steps in the Example data section below Robustness The software must allow for variations in tissue properties as well as staining cutting and imaging conditions In particular the software must be able to find and image the corresponding region in serial sections that may appear different due to staining artifacts damage during cutting or biological changes in the tissue If changes in the tissue or the microscope result in failures to target the correct tissue region or acquire high quality images these failures should be detected and corrected without the requirement of human intervention WaferMapper has been designed to meet these three goals Its central strategy is to first map the dataset using low resolution imaging so that the time consuming process of high resolution
53. re there have been significant improvements in SEM scan speed and more improvements are on the way The future development of WaferMapper will hopefully produce streamlined versions of the code as well as a version with fewer Matlab toolbox dependen cies At the time of the submission of this publication the most pressing areas for further code development are finding faster and more reliable methods of both focusing the microscope judging image quality and aligning section overviews and target points Table 1 A branch of the code being developed primarily by Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 16 Hayworth et al Imaging ATUM ultrathin section libraries Table 1 Breakdown of the time required for each step of data acquisition using ATUM SEM and WaferMapper Sample preparation Time varies with tissue size and staining method Tissue processing Sectioning Constructing wafers 1 2 weeks 8 30 s section 30 min wafer 100 500 sections per wafer Wafer mapping Time per wafer Full wafer image optical Wafer loading into chamber Full wafer image EM alternative to optical Section mapping Section overview image acquisition 3 min wafer 5 or 45 min wafer with or without load lock 20 60 min wafer Merlin Sigma 10 min wafer 30 120 min wafer depending on desired image quality Offline wafer mapping Time per wafer us
54. rtex tissue spanning 11 wafers The mapping procedure for this UTSL was based on full wafer SEM montage images of each wafer OFFLINE TARGET AND MONTAGE DEFINITION PHASE With the mapping data acquired the section overview images can now be assembled into a 3D map of the tissue volume in which high resolution imaging targets can be selected Align section overviews Each section overview image must be aligned to its neighbors across all wafers in order for the stack of images to be treated as an image volume Here we describe the cross correlation based alignment strategy that we have used to acquire all data sets to date For this method we find the y translation x translation and rotation that produces the highest cross correlation value between two images Typically the section overviews for a particular wafer are aligned on a non acquisition computer with access to the UTSL directory while other wafers are being imaged To align images the user first selects a template image either from the current wafer if this is the first wafer mapped in the UTSL or from the previous wafer which has already undergone section overview alignment By aligning each wafer to a section in the previous wafer a single aligned stack is created spanning all wafers in the UTSL At this stage in alignment each section on the wafer is aligned to the selected template image The section to section registra tion produced by this alignment is not as good as an
55. s in a desiccation or vacuum chamber Tissue contrast can be altered by the ini tial imaging process particularly at focus points however this change is usually not destructive as long as surface contamination of the wafer is minimal IMPLEMENTATION WaferMapper The software that oversees the steps outlined above is a MATLABG based program called WaferMapper The MATLAB script allows researchers with limited programing background to readily customize the code according to their particular needs The WaferMapper source code is freely accessible through a Google code SVN server https wafermapper googlecode com See user guide for Matlab toolbox dependencies and we encour age any interested parties to participate in the further develop ment of WaferMapper A detailed step by step user s manual is also available at this site In addition to the MATLAB code we provide two C wrap pers for interacting with the Zeiss SmartSEM API to control the microscope and the Fibics scan generator API for acquiring high pixel density images Although WaferMapper was writ ten to drive the Zeiss Fibics SEM system it can be adapted to other imaging systems with the addition of appropriate command wrappers For those who wish to build their own imaging soft ware the following description of our implementation should still be helpful as a practical guide to managing and imaging a UTSL OVERVIEW Figure 2B is a block diagram showing how Wa
56. tion of a 3 x 4 tile montage overlaying a target region scale bar 1 mm B Zooming in on the section overview display in WaferMapper allows the graphical display of the montage to be finely positioned relative to blood vessel and cell body landmarks visible at the resolution of the section overview images scale bar 100 pm C Zooming in again this time to a small region of one image from a larger stack of images automatically acquired by WaferMapper of this same UTSL The outlines of two neuronal processes sharing a synapse are shown highlighted in color scale bar 1 p D Graphic displaying every 10th image from this same aligned dataset acquired by WaferMapper ATUM sections were cut at 30 nm thickness thus these images are displayed here at 300 nm intervals through the tissue WaferMapper an imaging target point was selected from a region of the molecular layer of the cerebellum where the arbors of the Purkinje cells were parallel to the plane of microtome sectioning By selecting Target Point Setup gt Generate and Save List of Aligned Target Points the software was used to generate a sec ond local alignment suitable for directing the high resolution imaging Imaging Using WaferMapper s GUI display of the aligned overview stack we graphically defined a high resolution imaging montage that encompassed the arbors of several Purkinje cells Figure 9A The montage consisted of three rows and fi
57. ue tape This collection of 20 wafers is a single UltraThin Section Library UTSL containing over 3000 ultrathin sections representing a total tissue volume of over 0 2 mm8 millimeters each and of higher quality without tears etc than are obtained by manual collection for TEM A major challenge of the ATUM SEM approach is setting up many thousands of targeted image acquisitions from tissue sec tions spread across meters of ATUM collection tape To convert these sections into an image volume the ATUM s tape must be mounted in the SEM and a region of interest on a section must be positioned beneath the electron beam for imaging The cor responding region of interest must be found again and again on all subsequent sections Each section s target region must be posi tioned rotated and focused beneath the electron beam to obtain a high resolution image series Here we describe a semi automatic microscope control software package named WaferMapper that can orchestrate all of these steps to produce volume EM image sets from an ATUM tape With the proper software solution for handling the additional imaging complexity the ATUM SEM process has several poten tial advantages over alternative techniques The most obvious advantage over block face techniques is that the ATUM SEM technique does not destroy the tissue as it is being imaged Low resolution images of the entire tissue volume can therefore be taken relatively quickly
58. ve columns of tiles Each title consisted of 12 800 x 12 800 pixels resulting in a total 4nm resolution montage that covered about 250 x 150m of cerebel lum High resolution images were collected from 498 sections spanning three wafers and 15 um of cerebellum Figures 9B C The acquisition of the high resolution data required 100h of microscope time on a Zeiss Sigma Approximately one third of this acquisition time was consumed by scanning voxels at 10 MPS The remaining acquisition time was spent primarily on autofo cusing We found that this imaging time could be significantly reduced on a Zeiss Merlin due to its faster scan speed and larger depth of field FUTURE DIRECTIONS SOFTWARE DEVELOPMENT We wrote WaferMapper in MATLAB so that researchers who are not primarily programmers could readily add to the code accord ing to the needs of their experiments To date each large dataset acquired with WaferMapper has involved modifications of the code While the core version of WaferMapper we have released should be able to acquire most types of data we see collaborative development of the code as critical to WaferMapper s usefulness as new technologies and new uses for ultrathin section libraries evolve WaferMapper meets our initial simple goal of producing a data acquisition pipeline in which more time is spent acquir ing image montages than is spent finding the right place to image However even during the production of this softwa
59. wafer s metadata in principle contains all the information necessary for another lab with the same SEM setup to replicate an imaging run Quality check The ability to acquire a high quality large scale SEM dataset depends heavily on imaging with the correct focus and stigma tion settings The depth of field of the SEM is typically around 0 5 10 um depending on the imaging modality so that mul tiple focus points might be required to image a large montage Depending on the sample imaging conditions and stability of the microscope periodic refocusing and restigmating might be required regardless of the sample flatness To acquire images for days without human intervention WaferMapper uses a variety of strategies to minimize blurry images WaferMapper includes an algorithm that evaluates the quality of SEM images We designed this algorithm to be able to quickly judge the quality of very large images and then to base its evalu ation not on the average quality of the image but on the quality of the best regions of the image By only paying attention to areas with the most high frequency contrast quality values are less sen sitive to changes in tissue statistics that might come from blood vessels or section edges For the quality check to read and ana lyze images without adding to the tile to tile overhead time the quality check samples only a small fraction of the available pixels Quality check reads in a grid usually 200 x 200 of
60. wafer and obtain a section overview image see Figure 2A The overview image generally includes all of the tissue in the section typ ically several square millimeters while using a pixel size just small enough to identify features relevant to the future target ing of image volumes within the section commonly 1 ym pixel size After acquiring the overview images they are digitally regis tered to each other to remove effects of inter section rotation and translation The resultant aligned stack of overview images see Figure 2A constitutes a 3D coordinate map of tissue locations used for all subsequent navigation of the UTSL HIGH RESOLUTION IMAGE ACQUISITION With the low resolution UTSL overview map it becomes pos sible to select one or more target regions for higher resolution Frontiers in Neural Circuits www frontiersin org June 2014 Volume 8 Article 68 5 Hayworth et al Imaging ATUM ultrathin section libraries imaging throughout the volume A center position target point see Figure 2A for a targeted region is recorded and in some cases a second higher resolution local registration setting translation parameters only is performed now with the target position at its focus At high resolution a target region may require imaging a mosaic of multiple overlapping images arranged in rows and columns Imaging the target region therefore requires defining montage parameters i e size of the imagi

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