Unsupervised tissue image segmentation through object-oriented texture

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Unsupervised tissue image segmentation through object-oriented texture.pdf (1.02 MB)

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2010

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Abstract

This paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use this information in defining its homogeneity measures, but it also uses it in its region growing process. This algorithm has been implemented and tested. Its visual and quantitative results are compared with the previous study. The results show that the proposed segmentation algorithm is more robust in giving better accuracies with less number of segmented regions. © 2010 IEEE.

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2010 20th International Conference on Pattern Recognition

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IEEE

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Keywords

Image segmentation, Quantitative medical image analysis, Texture analysis, Medical image analysis, Object oriented, Quantitative result, Region growing, Segmentation algorithms, Segmented regions, Spatial informations, Texture analysis, Tissue components, Tissue image segmentation, Tissue images, Unsupervised segmentation, Algorithms, Image analysis, Information use, Medical imaging, Pattern recognition, Textures, Tissue, Image segmentation

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http://hdl.handle.net/11693/28520

Published Version (Please cite this version)

http://dx.doi.org/10.1109/ICPR.2010.616

Collections

Scholarly Publications - Computer Engineering
Scholarly Publications - UMRAM

Language

English

Type

Conference Paper