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Proceedings Paper

Computer-aided diagnosis of diagnostically challenging lesions in breast MRI: a comparison between a radiomics and a feature-selective approach
Author(s): Sebastian Hoffmann; Marc Lobbes; Ivo Houben; Katja Pinker-Domenig; Georg Wengert; Bernhard Burgeth; Uwe Meyer-Bäse; Guillaume Lemaitre; Anke Meyer-Baese
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Paper Abstract

Diagnostically challenging lesions pose a challenge both for the radiological reading and also for current CAD systems. They are not well-defined in both morphology (geometric shape) and kinetics (temporal enhancement) and pose a problem to lesion detection and classification. Their strong phenotypic differences can be visualized by MRI. Radiomics represents a novel approach to achieve a detailed quantification of the tumour phenotypes by analyzing a large number of image descriptors. In this paper, we apply a quantitative radiomics approach based on shape, texture and kinetics tumor features and evaluate it in comparison to a reduced-order feature approach in a computer-aided diagnosis system applied to diagnostically challenging lesions.

Paper Details

Date Published: 12 July 2016
PDF: 7 pages
Proc. SPIE 9871, Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016, 98710H (12 July 2016); doi: 10.1117/12.2228994
Show Author Affiliations
Sebastian Hoffmann, Florida State Univ. (United States)
Saarland Univ. (Germany)
Marc Lobbes, Maastricht Univ. Medical Ctr. (Netherlands)
Ivo Houben, Maastricht Univ. Medical Ctr. (Netherlands)
Katja Pinker-Domenig, Medical Univ. of Vienna (Austria)
Memorial Sloan-Kettering Cancer Ctr. (United States)
Georg Wengert, Medical Univ. of Vienna (Austria)
Bernhard Burgeth, Saarland Univ. (Germany)
Uwe Meyer-Bäse, Florida State Univ. (United States)
Guillaume Lemaitre, Univ. Bourgogne, LE2I, CNRS (France)
Anke Meyer-Baese, Florida State Univ. (United States)
Maastricht Univ. Medical Ctr. (Netherlands)


Published in SPIE Proceedings Vol. 9871:
Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016
Liyi Dai; Yufeng Zheng; Henry Chu; Anke D. Meyer-Bäse, Editor(s)

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