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Proceedings Paper

Computer-aided diagnosis of small lesions and non-masses in breast MRI
Author(s): Claudia Plant; Dat Ngo; Felix Retter; Olmo Zavala; Thomas Schlossbauer; Marc Lobbes; Maribel Lockwood; Anke Meyer-Bäse
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Paper Abstract

Small and non-mass-enhancing lesions are diagnostically challenging and easily missed in a routine clinical diagnosis. Compared to mass-enhancing lesions, they show fundamentally di®erent morphologies and kinetic characteristics. To overcome these limitations an automated analysis of such tumors is proposed to determine adequate shape and dynamical descriptors in order to capture this unique behavior. In the present paper, we evaluate several morphological and kinetic features as well combinations of those as potential shape and dynamic descriptors. We will show that for both types of lesions a combination of morphological and kinetic characteristics yields the highest AUC-values compared to dynamic or shape descriptors only. This suggests that for increasing diagnostic accuracy in breast MRI spatio-temporal descriptors for these lesions need to be included in an automated computer-aided system.

Paper Details

Date Published: 16 May 2012
PDF: 9 pages
Proc. SPIE 8367, Smart Biomedical and Physiological Sensor Technology IX, 83670A (16 May 2012); doi: 10.1117/12.921937
Show Author Affiliations
Claudia Plant, The Florida State Univ. (United States)
Dat Ngo, The Florida State Univ. (United States)
Felix Retter, Univ. of Saarbräucken (Germany)
Olmo Zavala, The Florida State Univ. (United States)
Thomas Schlossbauer, Univ. of Munich (Germany)
Marc Lobbes, Maastricht Univ. (Netherlands)
Maribel Lockwood, The Florida State Univ. (United States)
Anke Meyer-Bäse, The Florida State Univ. (United States)

Published in SPIE Proceedings Vol. 8367:
Smart Biomedical and Physiological Sensor Technology IX
Brian M. Cullum; Eric S. McLamore, Editor(s)

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