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Automatic Quantification of Microvessels Using Unsupervised Image Analysis

An automatic method for quantification of images of microvessels by computing area proportions and number of objects is presented. The objects are segmented from the background using dynamic thresholding of the average component size histogram. To be able to count the objects, fragmented objects are...

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Detalles Bibliográficos
Autores principales: Ranefall, Petter, Wester, Kenneth, Busch, Christer, Malmström, Per-Uno, Bengtsson, Ewert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 1998
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4611099/
https://www.ncbi.nlm.nih.gov/pubmed/10052632
http://dx.doi.org/10.1155/1998/490585
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author Ranefall, Petter
Wester, Kenneth
Busch, Christer
Malmström, Per-Uno
Bengtsson, Ewert
author_facet Ranefall, Petter
Wester, Kenneth
Busch, Christer
Malmström, Per-Uno
Bengtsson, Ewert
author_sort Ranefall, Petter
collection PubMed
description An automatic method for quantification of images of microvessels by computing area proportions and number of objects is presented. The objects are segmented from the background using dynamic thresholding of the average component size histogram. To be able to count the objects, fragmented objects are connected, all objects are filled, and touching objects are separated using a watershed segmentation algorithm. The method is fully automatic and robust with respect to illumination and focus settings. A test set consisting of images grabbed with different focus and illumination for each field of view, was used to test the method, and the proposed method showed less variation than the intraoperator variation using manual threshold. Further, the method showed good correlation to manual object counting (r = 0.80) on an other test set.
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spelling pubmed-46110992016-01-12 Automatic Quantification of Microvessels Using Unsupervised Image Analysis Ranefall, Petter Wester, Kenneth Busch, Christer Malmström, Per-Uno Bengtsson, Ewert Anal Cell Pathol Other An automatic method for quantification of images of microvessels by computing area proportions and number of objects is presented. The objects are segmented from the background using dynamic thresholding of the average component size histogram. To be able to count the objects, fragmented objects are connected, all objects are filled, and touching objects are separated using a watershed segmentation algorithm. The method is fully automatic and robust with respect to illumination and focus settings. A test set consisting of images grabbed with different focus and illumination for each field of view, was used to test the method, and the proposed method showed less variation than the intraoperator variation using manual threshold. Further, the method showed good correlation to manual object counting (r = 0.80) on an other test set. IOS Press 1998 1998-01-01 /pmc/articles/PMC4611099/ /pubmed/10052632 http://dx.doi.org/10.1155/1998/490585 Text en Copyright © 1998 Hindawi Publishing Corporation.
spellingShingle Other
Ranefall, Petter
Wester, Kenneth
Busch, Christer
Malmström, Per-Uno
Bengtsson, Ewert
Automatic Quantification of Microvessels Using Unsupervised Image Analysis
title Automatic Quantification of Microvessels Using Unsupervised Image Analysis
title_full Automatic Quantification of Microvessels Using Unsupervised Image Analysis
title_fullStr Automatic Quantification of Microvessels Using Unsupervised Image Analysis
title_full_unstemmed Automatic Quantification of Microvessels Using Unsupervised Image Analysis
title_short Automatic Quantification of Microvessels Using Unsupervised Image Analysis
title_sort automatic quantification of microvessels using unsupervised image analysis
topic Other
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4611099/
https://www.ncbi.nlm.nih.gov/pubmed/10052632
http://dx.doi.org/10.1155/1998/490585
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