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Abstract #2314

Classification of Breast Magnetic Resonance Imaging Using 3D Convolution Neural Network: A Pilot Study

Cindy Xue1, Gladys Lo1, Victor Ai1, Oilei O.L Wong1, Max W.K Law1, and Jing Yuan1
1Hong Kong Sanatorium and Hospital, Hong Kong, Hong Kong

BIRADS classification is one of the standard of reporting breast MRI. It reveals the information about the likelihood of cancer and management recommendation for the patients. In this study, we aimed to develop and evaluate a 3D convolution neural network (CNN) for breast MRI BIRADS classification. This 3D CNN network was evaluated and it achieved overall 90% classification accuracy. In particular, the network also has high sensitivity (100%) of highly suspicious of malignancy findings. The results suggested that a deep learning-based computerized tool might be useful in BIRADS-MRI classification.

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