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Abstract #2716

A multi-channel convolutional neural network for segmentation of breast lesions in DCE-MRI

Karl Spuhler1, Mario Serrano Sosa1, Jie Ding1, Tim Duong2, and Chuan Huang1,2,3

1Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States, 2Radiology, Stony Brook Medicine, Stony Brook, NY, United States, 3Psychiatry, Stony Brook Medicine, Stony Brook, NY, United States

Radiomics offers a highly quantitative and high-dimensional view of the tumor microenvironment which no conventional imaging technique allows. It is the ideal strategy for personalizing care in heterogeneous cancers such as in the breast. Most approaches require time consuming, manual region of interest segmentation. Here, we present a fast and accurate neural network approach for breast lesion segmentation which can be adapted to accept any number of imaging modalities and shows reliability across many types of lesion.

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