Ensemble Multi-Path U-net Segmentation Algorithm for Breast Lesion based on Multi-Modality Image

The 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.