Paper
30 March 2007 A hybrid active contour model for mass detection in digital breast tomosynthesis
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Abstract
In this paper we present a novel approach for mass contour detection for 3D computer-aided detection (CAD) in digital breast tomosynthesis (DBT) data-sets. A hybrid active contour model, working directly on the projected views, is proposed. The responses of a wavelet filter applied on the projections are thresholded and combined to obtain markers for mass candidates. The contours of markers are extracted and serve as initialization for the active contour model, which is then used to extract mass contours in DBT projection images. A hybrid model is presented, taking into account several image-based external forces and implemented using a level-set formulation. A feature vector is computed from the detected contour, which may serve as input to a dedicated classifier. The segmentation method is applied to simulated images and to clinical cases. Image segmentation results are presented and compared to two standard active contour models. Evaluation of the performance on clinical data is obtained by comparison to manual segmentation by an expert. Performance on simulated images and visual performance assessment provide further illustration of the performance of the presented approach.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gero Peters, Serge Muller, Bénédicte Grosjean, Sylvain Bernard, and Isabelle Bloch "A hybrid active contour model for mass detection in digital breast tomosynthesis", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65141V (30 March 2007); https://doi.org/10.1117/12.709593
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Cited by 9 scholarly publications.
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KEYWORDS
Image segmentation

Digital breast tomosynthesis

Breast

Data modeling

Image filtering

Mammography

Wavelets

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