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Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking

A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called “Segmentation by Weighted Aggregation” technique, which itself is based on Algebraic Multigrid methods. The variant of the method used i...

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Detalles Bibliográficos
Autores principales: Inglis, Tiffany, De Sterck, Hans, Sanders, Geoffrey, Djambazian, Haig, Sladek, Robert, Sundararajan, Saravanan, Hudson, Thomas J.
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2866245/
https://www.ncbi.nlm.nih.gov/pubmed/20467468
http://dx.doi.org/10.1155/2010/582760
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author Inglis, Tiffany
De Sterck, Hans
Sanders, Geoffrey
Djambazian, Haig
Sladek, Robert
Sundararajan, Saravanan
Hudson, Thomas J.
author_facet Inglis, Tiffany
De Sterck, Hans
Sanders, Geoffrey
Djambazian, Haig
Sladek, Robert
Sundararajan, Saravanan
Hudson, Thomas J.
author_sort Inglis, Tiffany
collection PubMed
description A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called “Segmentation by Weighted Aggregation” technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant “saliency measure” is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments (“object tunnels”) that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system.
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spelling pubmed-28662452010-05-13 Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking Inglis, Tiffany De Sterck, Hans Sanders, Geoffrey Djambazian, Haig Sladek, Robert Sundararajan, Saravanan Hudson, Thomas J. Int J Biomed Imaging Research Article A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called “Segmentation by Weighted Aggregation” technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant “saliency measure” is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments (“object tunnels”) that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system. Hindawi Publishing Corporation 2010 2010-04-27 /pmc/articles/PMC2866245/ /pubmed/20467468 http://dx.doi.org/10.1155/2010/582760 Text en Copyright © 2010 Tiffany Inglis et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Inglis, Tiffany
De Sterck, Hans
Sanders, Geoffrey
Djambazian, Haig
Sladek, Robert
Sundararajan, Saravanan
Hudson, Thomas J.
Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking
title Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking
title_full Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking
title_fullStr Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking
title_full_unstemmed Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking
title_short Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking
title_sort multilevel space-time aggregation for bright field cell microscopy segmentation and tracking
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2866245/
https://www.ncbi.nlm.nih.gov/pubmed/20467468
http://dx.doi.org/10.1155/2010/582760
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