Contour-propagation algorithms for semi-automated reconstruction of neural processes

A new technique, “serial block face scanning electron microscopy” (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, i...

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Veröffentlicht in:	Journal of neuroscience methods Jg. 167; H. 2; S. 349 - 357
Hauptverfasser:	Macke, Jakob H., Maack, Nina, Gupta, Rocky, Denk, Winfried, Schölkopf, Bernhard, Borst, Alexander
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 30.01.2008
Schlagworte:	Algorithm Algorithms Animals Automatic Data Processing - methods Brain - cytology Brain - ultrastructure Circuit reconstruction software Contour detection Fly visual system Image Processing, Computer-Assisted Image segmentation Insecta Microscopy, Electron, Scanning - instrumentation Neural circuits Neurons - ultrastructure Serial block-face scanning electron microscopy Image segmentation Neural circuits Contour detection Fly visual system Circuit reconstruction software Serial block-face scanning electron microscopy Algorithm
ISSN:	0165-0270, 1872-678X
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Abstract	A new technique, “serial block face scanning electron microscopy” (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, including synaptic structures, which should make it possible to obtain detailed anatomical knowledge of complete neuronal circuits. Such an image stack contains several thousands of images and is recorded with a minimal voxel size of 10–20 nm in the x- and y-direction and 30 nm in z-direction. Consequently, a tissue block of 1 mm 3(the approximate volume of the Calliphora vicina brain) will produce several hundred terabytes of data. Therefore, highly automated 3D reconstruction algorithms are needed. As a first step in this direction we have developed semi-automated segmentation algorithms for a precise contour tracing of cell membranes. These algorithms were embedded into an easy-to-operate user interface, which allows direct 3D observation of the extracted objects during the segmentation of image stacks. Compared to purely manual tracing, processing time is greatly accelerated.
AbstractList	A new technique, “serial block face scanning electron microscopy” (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, including synaptic structures, which should make it possible to obtain detailed anatomical knowledge of complete neuronal circuits. Such an image stack contains several thousands of images and is recorded with a minimal voxel size of 10–20 nm in the x- and y-direction and 30 nm in z-direction. Consequently, a tissue block of 1 mm 3(the approximate volume of the Calliphora vicina brain) will produce several hundred terabytes of data. Therefore, highly automated 3D reconstruction algorithms are needed. As a first step in this direction we have developed semi-automated segmentation algorithms for a precise contour tracing of cell membranes. These algorithms were embedded into an easy-to-operate user interface, which allows direct 3D observation of the extracted objects during the segmentation of image stacks. Compared to purely manual tracing, processing time is greatly accelerated. A new technique, "serial block face scanning electron microscopy" (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, including synaptic structures, which should make it possible to obtain detailed anatomical knowledge of complete neuronal circuits. Such an image stack contains several thousands of images and is recorded with a minimal voxel size of 10-20 nm in the x- and y-direction and 30 nm in z-direction. Consequently, a tissue block of 1 mm(3)(the approximate volume of the Calliphora vicina brain) will produce several hundred terabytes of data. Therefore, highly automated 3D reconstruction algorithms are needed. As a first step in this direction we have developed semi-automated segmentation algorithms for a precise contour tracing of cell membranes. These algorithms were embedded into an easy-to-operate user interface, which allows direct 3D observation of the extracted objects during the segmentation of image stacks. Compared to purely manual tracing, processing time is greatly accelerated.A new technique, "serial block face scanning electron microscopy" (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, including synaptic structures, which should make it possible to obtain detailed anatomical knowledge of complete neuronal circuits. Such an image stack contains several thousands of images and is recorded with a minimal voxel size of 10-20 nm in the x- and y-direction and 30 nm in z-direction. Consequently, a tissue block of 1 mm(3)(the approximate volume of the Calliphora vicina brain) will produce several hundred terabytes of data. Therefore, highly automated 3D reconstruction algorithms are needed. As a first step in this direction we have developed semi-automated segmentation algorithms for a precise contour tracing of cell membranes. These algorithms were embedded into an easy-to-operate user interface, which allows direct 3D observation of the extracted objects during the segmentation of image stacks. Compared to purely manual tracing, processing time is greatly accelerated. A new technique, "serial block face scanning electron microscopy" (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, including synaptic structures, which should make it possible to obtain detailed anatomical knowledge of complete neuronal circuits. Such an image stack contains several thousands of images and is recorded with a minimal voxel size of 10-20 nm in the x- and y-direction and 30 nm in z-direction. Consequently, a tissue block of 1 mm(3)(the approximate volume of the Calliphora vicina brain) will produce several hundred terabytes of data. Therefore, highly automated 3D reconstruction algorithms are needed. As a first step in this direction we have developed semi-automated segmentation algorithms for a precise contour tracing of cell membranes. These algorithms were embedded into an easy-to-operate user interface, which allows direct 3D observation of the extracted objects during the segmentation of image stacks. Compared to purely manual tracing, processing time is greatly accelerated.
Author	Denk, Winfried Borst, Alexander Macke, Jakob H. Gupta, Rocky Schölkopf, Bernhard Maack, Nina
Author_xml	– sequence: 1 givenname: Jakob H. surname: Macke fullname: Macke, Jakob H. email: jakob@tuebingen.mpg.de organization: Max Planck Institute for Biological Cybernetics, Spemannstraße 38, D-72076 Tübingen, Germany – sequence: 2 givenname: Nina surname: Maack fullname: Maack, Nina email: maack@neuro.mpg.de organization: Max Planck Institute of Neurobiology, Department of Systems and Computational Neurobiology, Am Klopferspitz 18, D-82152 Martinsried, Germany – sequence: 3 givenname: Rocky surname: Gupta fullname: Gupta, Rocky email: Rocky@iitk.ac.in organization: Indian Institute of Technology Kanpur, Department of Electrical Engineering, Kanpur, India – sequence: 4 givenname: Winfried surname: Denk fullname: Denk, Winfried email: denk@mpimf-heidelberg.mpg.de organization: Max-Planck-Institute for Medical Research, Jahnstraße 29, D-69120 Heidelberg, Germany – sequence: 5 givenname: Bernhard surname: Schölkopf fullname: Schölkopf, Bernhard email: bs@tuebingen.mpg.de organization: Max Planck Institute for Biological Cybernetics, Spemannstraße 38, D-72076 Tübingen, Germany – sequence: 6 givenname: Alexander surname: Borst fullname: Borst, Alexander email: borst@neuro.mpg.de organization: Max Planck Institute of Neurobiology, Department of Systems and Computational Neurobiology, Am Klopferspitz 18, D-82152 Martinsried, Germany
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Cites_doi	10.1007/s11263-005-3676-z 10.1016/j.neuroimage.2004.06.047 10.1162/089976602753712945 10.1109/83.902291 10.1007/s00359-002-0316-8 10.1147/rd.191.0002 10.1109/TITB.2002.1006304 10.1016/j.conb.2006.08.010 10.1109/TPAMI.2002.1046177 10.1371/journal.pbio.0020329 10.1080/01431160512331326747 10.1002/cpa.3160420503 10.1109/TPAMI.2006.161 10.1080/09548980500275378 10.1109/34.56205
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Keywords	Image segmentation Neural circuits Contour detection Fly visual system Circuit reconstruction software Serial block-face scanning electron microscopy Algorithm
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Snippet	A new technique, “serial block face scanning electron microscopy” (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning... A new technique, "serial block face scanning electron microscopy" (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning...
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SubjectTerms	Algorithm Algorithms Animals Automatic Data Processing - methods Brain - cytology Brain - ultrastructure Circuit reconstruction software Contour detection Fly visual system Image Processing, Computer-Assisted Image segmentation Insecta Microscopy, Electron, Scanning - instrumentation Neural circuits Neurons - ultrastructure Serial block-face scanning electron microscopy
Title	Contour-propagation algorithms for semi-automated reconstruction of neural processes
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