Segmenting neurons in electronic microscopy via geometric tracing

Vázquez, Luis - Sapiro, Guillermo - Randall, Gregory

Resumen:

Describes a system that is being used for the segmentation of neurons in images obtained from electronic microscopy. These images are extremely noisy, and ordinary active contours techniques detect spurious objects and fail to detect the neuron boundaries. The algorithm here described is based on combining robust anisotropic diffusion with minimal weighted-path computations. After the image is regularized via anisotropic diffusion, the user clicks points on the boundary of the desired object, and the algorithm completes the boundary between those points. This tracing is based on computing paths of minimal weighted distance, where the weight is given by the image edge content. Thanks to advanced numerical algorithms, the algorithm is very fast and accurate. The authors compare their results with those obtained with PictureIt, a commercially available general purpose image processing package developed by Microsoft.


Detalles Bibliográficos
1998
Electronic microscopy
Neurons
Anisotropic diffusion
Weighted distances
Geometric tracing
Segmentation
Curve evolution
PROCESAMIENTO de SEÑALES
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/20768
Acceso abierto
Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)
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author Vázquez, Luis
author2 Sapiro, Guillermo
Randall, Gregory
author2_role author
author
author_facet Vázquez, Luis
Sapiro, Guillermo
Randall, Gregory
author_role author
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collection COLIBRI
dc.creator.none.fl_str_mv Vázquez, Luis
Sapiro, Guillermo
Randall, Gregory
dc.date.accessioned.none.fl_str_mv 2019-05-29T15:28:11Z
dc.date.available.none.fl_str_mv 2019-05-29T15:28:11Z
dc.date.issued.es.fl_str_mv 1998
dc.date.submitted.es.fl_str_mv 20190528
dc.description.abstract.none.fl_txt_mv Describes a system that is being used for the segmentation of neurons in images obtained from electronic microscopy. These images are extremely noisy, and ordinary active contours techniques detect spurious objects and fail to detect the neuron boundaries. The algorithm here described is based on combining robust anisotropic diffusion with minimal weighted-path computations. After the image is regularized via anisotropic diffusion, the user clicks points on the boundary of the desired object, and the algorithm completes the boundary between those points. This tracing is based on computing paths of minimal weighted distance, where the weight is given by the image edge content. Thanks to advanced numerical algorithms, the algorithm is very fast and accurate. The authors compare their results with those obtained with PictureIt, a commercially available general purpose image processing package developed by Microsoft.
dc.description.es.fl_txt_mv Postprint
dc.identifier.citation.es.fl_str_mv Vázquez, Luis, Sapiro, Guillermo, Randall, Gregory. Segmenting neurons in electronic microscopy via geometric tracing [en línea] International Conference on Image Processing, 1998.
dc.identifier.doi.es.fl_str_mv DOI: 10.1109/ICIP.1998.999070
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/20768
dc.language.iso.none.fl_str_mv en
eng
dc.publisher.es.fl_str_mv IEEE
dc.relation.ispartof.es.fl_str_mv International Conference on Image Processing, 1998. Proceedings
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv Electronic microscopy
Neurons
Anisotropic diffusion
Weighted distances
Geometric tracing
Segmentation
Curve evolution
dc.subject.other.es.fl_str_mv PROCESAMIENTO de SEÑALES
dc.title.none.fl_str_mv Segmenting neurons in electronic microscopy via geometric tracing
dc.type.es.fl_str_mv Artículo
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description Postprint
eu_rights_str_mv openAccess
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identifier_str_mv Vázquez, Luis, Sapiro, Guillermo, Randall, Gregory. Segmenting neurons in electronic microscopy via geometric tracing [en línea] International Conference on Image Processing, 1998.
DOI: 10.1109/ICIP.1998.999070
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
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publishDate 1998
reponame_str COLIBRI
repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)
spelling 2019-05-29T15:28:11Z2019-05-29T15:28:11Z199820190528Vázquez, Luis, Sapiro, Guillermo, Randall, Gregory. Segmenting neurons in electronic microscopy via geometric tracing [en línea] International Conference on Image Processing, 1998.https://hdl.handle.net/20.500.12008/20768DOI: 10.1109/ICIP.1998.999070PostprintDescribes a system that is being used for the segmentation of neurons in images obtained from electronic microscopy. These images are extremely noisy, and ordinary active contours techniques detect spurious objects and fail to detect the neuron boundaries. The algorithm here described is based on combining robust anisotropic diffusion with minimal weighted-path computations. After the image is regularized via anisotropic diffusion, the user clicks points on the boundary of the desired object, and the algorithm completes the boundary between those points. This tracing is based on computing paths of minimal weighted distance, where the weight is given by the image edge content. Thanks to advanced numerical algorithms, the algorithm is very fast and accurate. The authors compare their results with those obtained with PictureIt, a commercially available general purpose image processing package developed by Microsoft.Made available in DSpace on 2019-05-29T15:28:11Z (GMT). No. of bitstreams: 5 VSR98.pdf: 1747097 bytes, checksum: d0158dc47a77f5c007f4ee258589ca94 (MD5) license_text: 21936 bytes, checksum: 9833653f73f7853880c94a6fead477b1 (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) license.txt: 4194 bytes, checksum: 7f2e2c17ef6585de66da58d1bfa8b5e1 (MD5) Previous issue date: 1998enengIEEEInternational Conference on Image Processing, 1998. ProceedingsLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)Electronic microscopyNeuronsAnisotropic diffusionWeighted distancesGeometric tracingSegmentationCurve evolutionPROCESAMIENTO de SEÑALESSegmenting neurons in electronic microscopy via geometric tracingArtículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaVázquez, LuisSapiro, GuillermoRandall, GregoryProcesamiento de SeñalesTratamiento de 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- Universidad de la Repúblicafalse
spellingShingle Segmenting neurons in electronic microscopy via geometric tracing
Vázquez, Luis
Electronic microscopy
Neurons
Anisotropic diffusion
Weighted distances
Geometric tracing
Segmentation
Curve evolution
PROCESAMIENTO de SEÑALES
status_str publishedVersion
title Segmenting neurons in electronic microscopy via geometric tracing
title_full Segmenting neurons in electronic microscopy via geometric tracing
title_fullStr Segmenting neurons in electronic microscopy via geometric tracing
title_full_unstemmed Segmenting neurons in electronic microscopy via geometric tracing
title_short Segmenting neurons in electronic microscopy via geometric tracing
title_sort Segmenting neurons in electronic microscopy via geometric tracing
topic Electronic microscopy
Neurons
Anisotropic diffusion
Weighted distances
Geometric tracing
Segmentation
Curve evolution
PROCESAMIENTO de SEÑALES
url https://hdl.handle.net/20.500.12008/20768