Identification of corresponding lesions in multiple mammographic views using star-shaped iso-contours

Rafael Wiemker; Dominik Kutra; Harald Heese; Thomas Buelow

doi:10.1117/12.2043218

24 March 2014 Identification of corresponding lesions in multiple mammographic views using star-shaped iso-contours

Rafael Wiemker, Dominik Kutra, Harald Heese, Thomas Buelow

Proceedings Volume 9035, Medical Imaging 2014: Computer-Aided Diagnosis; 90351A (2014) https://doi.org/10.1117/12.2043218
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

It is common practice to assess lesions in two different mammographic views of each breast: medio-lateral oblique (MLO) and cranio-caudal (CC). We investigate methods that aim at automatic identification of a lesion which was indicated by the user in one view in the other view of the same breast. Automated matching of user indicated lesions has slightly different objectives than lesion segmentation or matching for improved computer aided detection, leading to different algorithmic choices. A novel computationally efficient algorithm is presented which is based on detection of star-shaped iso-contours with high sphericity and local consistency. The lesion likelihood is derived from a purely geometry based figure of merit and thus is invariant against monotonous intensity transformations (e.g. non-linear LUTs).Validation was carried out by virtue of FROC curves on a public database consisting of entirely digital mammograms with expert-delineated match pairs, showing superior performance as compared to gradient-based minimum cost path algorithms, with computation times faster by an order of magnitude and the potential of being fully parallelizable for GPU implementations.

Citation Download Citation

Rafael Wiemker, Dominik Kutra, Harald Heese, and Thomas Buelow "Identification of corresponding lesions in multiple mammographic views using star-shaped iso-contours", Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90351A (24 March 2014); https://doi.org/10.1117/12.2043218

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