Interactive breast cancer segmentation based on relevance feedback: from user-centered design to evaluation

A. Gouze; S. Kieffer; C. Van Brussel; R. Moncarey; A. Grivegnée; B. Macq

doi:10.1117/12.813538

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3 March 2009 Interactive breast cancer segmentation based on relevance feedback: from user-centered design to evaluation

A. Gouze, S. Kieffer, C. Van Brussel, R. Moncarey, A. Grivegnée, B. Macq

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Proceedings Volume 7260, Medical Imaging 2009: Computer-Aided Diagnosis; 726021 (2009) https://doi.org/10.1117/12.813538
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Computer systems play an important role in medical imaging industry since radiologists depend on it for visualization, interpretation, communication and archiving. In particular, computer-aided diagnosis (CAD) systems help in lesion detection tasks. This paper presents the design and the development of an interactive segmentation tool for breast cancer screening and diagnosis. The tool conception is based upon a user-centered approach in order to ensure that the application is of real benefit to radiologists. The analysis of user expectations, workflow and decision-making practices give rise to the need for an interactive reporting system based on the BIRADS, that would not only include the numerical features extracted from the segmentation of the findings in a structured manner, but also support human relevance feedback as well. This way, the numerical results from segmentation can be either validated by end-users or enhanced thanks to domain-experts subjective interpretation. Such a domain-expert centered system requires the segmentation to be sufficiently accurate and locally adapted, and the features to be carefully selected in order to best suit user's knowledge and to be of use in enhancing segmentation. Improving segmentation accuracy with relevance feedback and providing radiologists with a user-friendly interface to support image analysis are the contributions of this work. The preliminary result is first the tool conception, and second the improvement of the segmentation precision.

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A. Gouze, S. Kieffer, C. Van Brussel, R. Moncarey, A. Grivegnée, and B. Macq "Interactive breast cancer segmentation based on relevance feedback: from user-centered design to evaluation", Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 726021 (3 March 2009); https://doi.org/10.1117/12.813538

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