We propose a novel, simple and effective method to integrate lesion prior and
a 3D U-Net for improving brain tumor segmentation. First, we utilize the
ground-truth brain tumor lesions from a group of patients to generate the
heatmaps of different types of lesions. These heatmaps are used to create the
volume-of-interest (VOI) map which contains prior information about brain tumor
lesions. The VOI map is then integrated with the multimodal MR images and input
to a 3D U-Net for segmentation. The proposed method is evaluated on a public
benchmark dataset, and the experimental results show that the proposed feature
fusion method achieves an improvement over the baseline methods. In addition,
our proposed method also achieves a competitive performance compared to
state-of-the-art methods.Comment: 5 pages, 4 figures, 1 table, LNCS forma