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Proceedings Paper

Automated malignancy detection in breast histopathological images
Author(s): Andrei Chekkoury; Parmeshwar Khurd; Jie Ni; Claus Bahlmann; Ali Kamen; Amar Patel; Leo Grady; Maneesh Singh; Martin Groher; Nassir Navab; Elizabeth Krupinski; Jeffrey Johnson; Anna Graham; Ronald Weinstein
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Paper Abstract

Detection of malignancy from histopathological images of breast cancer is a labor-intensive and error-prone process. To streamline this process, we present an efficient Computer Aided Diagnostic system that can differentiate between cancerous and non-cancerous H&E (hemotoxylin&eosin) biopsy samples. Our system uses novel textural, topological and morphometric features taking advantage of the special patterns of the nuclei cells in breast cancer histopathological images. We use a Support Vector Machine classifier on these features to diagnose malignancy. In conjunction with the maximum relevance - minimum redundancy feature selection technique, we obtain high sensitivity and specificity. We have also investigated the effect of image compression on classification performance.

Paper Details

Date Published: 23 February 2012
PDF: 13 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 831515 (23 February 2012); doi: 10.1117/12.911643
Show Author Affiliations
Andrei Chekkoury, Siemens Corporate Research (United States)
Parmeshwar Khurd, Siemens Corporate Research (United States)
Jie Ni, Siemens Corporate Research (United States)
Claus Bahlmann, Siemens Corporate Research (United States)
Ali Kamen, Siemens Corporate Research (United States)
Amar Patel, Siemens Corporate Research (United States)
Leo Grady, Siemens Corporate Research (United States)
Maneesh Singh, Siemens Corporate Research (United States)
Martin Groher, Technische Univ. München (Germany)
Nassir Navab, Technische Univ. München (Germany)
Elizabeth Krupinski, The Univ. of Arizona (United States)
Jeffrey Johnson, Siemens Corporate Research (United States)
Anna Graham, The Univ. of Arizona (United States)
Ronald Weinstein, The Univ. of Arizona (United States)

Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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