Color graphs for automated cancer diagnosis and grading

Date
2010-03
Authors
Altunbay, D.
Cigir, C.
Sokmensuer, C.
Gunduz Demir, C.
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
IEEE Transactions on Biomedical Engineering
Print ISSN
0018-9294
Electronic ISSN
1558-2531
Publisher
Institute of Electrical and Electronics Engineers
Volume
57
Issue
3
Pages
665 - 674
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
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Abstract

This paper reports a new structural method to mathematically represent and quantify a tissue for the purpose of automated and objective cancer diagnosis and grading. Unlike the previous structural methods, which quantify a tissue considering the spatial distributions of its cell nuclei, the proposed method relies on the use of distributions of multiple tissue components for the representation. To this end, it constructs a graph on multiple tissue components and colors its edges depending on the component types of their endpoints. Subsequently, it extracts a new set of structural features from these color graphs and uses these features in the classification of tissues. Working with the images of colon tissues, our experiments demonstrate that the color-graph approach leads to 82.65% test accuracy and that it significantly improves the performance of its counterparts. © 2006 IEEE.

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Keywords
Biomedical image processing, Cancer, Graph theory, Histopathological image analysis, Image representations, Medical diagnosis, Automated cancer diagnosis, Cancer diagnosis, Cell nucleus, Colon tissues, Color graphs
Citation
Published Version (Please cite this version)