Keywords: Breast, Machine Learning/Artificial Intelligence, Deep LearningThe multimodal MRI data is often ultilized for breast cancer analysis, and by now still difficult and inefficient to explored by segmentation algorithms. In this paper, we propose a MP-Unet based on U-net convolutional neural network, which can effectively ensemble multiple inputs of modal data and obtain accuracy segmentation results at the end. In MP-Unet, we reused some good quality modal data for training. The multiple MP-Unet models are further integrated based on Bagging algorithm to improve the segmentation accuracy of lesions. Experiments suggest that our proposed method has a huge performance improvement.
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