Generic Neighborhood Operators
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Approaches for automated detection and classification of masses in mammograms
Pattern Recognition
Fast detection of convergence areas in digital breast tomosynthesis
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Fast detection of convergence areas in digital breast tomosynthesis
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Spiculated lesions and architectural distortions detection in digital breast tomosynthesis datasets
IWDM'10 Proceedings of the 10th international conference on Digital Mammography
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In this paper we propose a fast method to detect spiculated lesions and architectural distortions in Digital Breast Tomosynthesis datasets. This approach relies on an a contrario modeling of the problem. First, an indicator corresponding to the convergence of structures is defined, then the a contrario framework is used to set a threshold on it in order to detect zones where its value is unlikely. We propose, as a main contribution of this paper, a fast algorithm to implement this method, which significantly reduces its computational cost. The method was evaluated on 38 breasts (10 containing a lesion), and a sensitivity of 0.8 at 1.68 false positive per breast was obtained.