28 February 2013 Finding lesion correspondences in different views of automated 3D breast ultrasound
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Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 86701N (2013) https://doi.org/10.1117/12.2007475
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Screening with automated 3D breast ultrasound (ABUS) is gaining popularity. However, the acquisition of multiple views required to cover an entire breast makes radiologic reading time-consuming. Linking lesions across views can facilitate the reading process. In this paper, we propose a method to automatically predict the position of a lesion in the target ABUS views, given the location of the lesion in a source ABUS view. We combine features describing the lesion location with respect to the nipple, the transducer and the chestwall, with features describing lesion properties such as intensity, spiculation, blobness, contrast and lesion likelihood. By using a grid search strategy, the location of the lesion was predicted in the target view. Our method achieved an error of 15.64 mm±16.13 mm. The error is small enough to help locate the lesion with minor additional interaction.
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Tao Tan, Bram Platel, Michael Hicks, Ritse M. Mann, Nico Karssemeijer, "Finding lesion correspondences in different views of automated 3D breast ultrasound", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86701N (28 February 2013); doi: 10.1117/12.2007475; https://doi.org/10.1117/12.2007475
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