Graph-based tools for microscopic cellular image segmentation

VT Ta, O Lézoray, A Elmoataz, S Schüpp - Pattern Recognition, 2009 - Elsevier
Pattern Recognition, 2009Elsevier
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 …
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.
Elsevier
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