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Graph-based tools for microscopic cellular image segmentation

delete2009-06-01
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O
Olivier Lézoray
A
Abderrahim Elmoataz
DOI:10.1016/j.patcog.2008.10.029delete
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Abstract

Abstract

En 中文
We propose a framework of graph-based tools for the segmentation of microscopic cellular images. This framework is based on an object oriented analysis of imaging problems in pathology. Our graph tools rely on a general formulation of discrete functional regularization on weighted graphs of arbitrary topology. It leads to a set of useful tools which can be combined together to address various image segmentation problems in pathology. To provide fast image segmentation algorithms, we also propose an image simplification based on graphs as a pre processing step. The abilities of this set of image processing discrete tools are illustrated through automatic and interactive segmentation schemes for color cytological and histological images segmentation problems. (C) 2008 Elsevier Ltd. All rights reserved.
Keywords:
Cytological and histological images
Pathology
Weighted graphs
Image processing tools
Discrete regularization
Fast image processing
Automatic and interactive segmentation schemes
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Journal

Pattern Recognition cover
Pattern Recognition
IF:
7.6
Papers:
1.3W
Citations:
4.5W

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U
universite de caen normandie
Scholars:
8.0K
Papers: 5.3K
Citations: 4