Analyzing tree-shape anatomical structures using topological descriptors of branching and ensemble of classifiers

• Autorzy: Skoura A. , Bakic P.R. , Megalooikonomou V.
• Języki publikacji: EN

Abstrakty

EN

The analysis of anatomical tree-shape structures visualized in medical images provides insight into the relationship between tree topology and pathology of the corresponding organs. In this paper, we propose three methods to extract descriptive features of the branching topology; the asymmetry index, the encoding of branching patterns using a node labeling scheme and an extension of the Sholl analysis. Based on these descriptors, we present classification schemes for tree topologies with respect to the underlying pathology. Moreover, we present a classifier ensemble approach which combines the predictions of the individual classifiers to optimize the classification accuracy. We applied the proposed methodology to a dataset of x-ray galactograms, medical images which visualize the breast ductal tree, in order to recognize images with radiological findings regarding breast cancer. The experimental results demonstrate the effectiveness of the proposed framework compared to state-of-the-art techniques suggesting that the proposed descriptors provide more valuable information regarding the topological patterns of ductal trees and indicating the potential of facilitating early breast cancer diagnosis.

Słowa kluczowe

EN

image classification; medical decision systems; computer aided diagnosis; tree-shape topology; ensemble of classifiers

• Wydawca: Komisja Informatyki Polskiej Akademii Nauk, Oddział w Gdańsku
• Czasopismo: Journal of Theoretical and Applied Computer Science
• Rocznik: 2013
• Tom: Vol. 7, nr 1
• Strony: 3--19
• Opis fizyczny: Bibliogr. 36 poz., rys., tab.

Twórcy

autor

Skoura A.

• Computer Engineering and Informatics Department, University of Patras, Greece

autor

Bakic P.R.

• Department of Radiology, University of Pennsylvania, Philadelphia, USA

autor

Megalooikonomou V.

• Computer Engineering and Informatics Department, University of Patras, Greece
• Center for Data Analytics and Biomedical Informatics, Temple University, USA

Bibliografia

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