We proposed a Mutual Communicated Deep learning Segmentation and Classification Network (MC-DSCN) for prostate cancer based on multi-parametric MRI. The network consists of three mutual bootstrapping components: the coarse segmentation component provides coarse-mask information for the classification component, the mask-guided classification component based on multi-parametric MRI generates the location maps, and the fine segmentation component guided by the located maps. By jointly performing segmentation based on pixel-level information and classification based on image-level information, both segmentation and classification accuracy are improved simultaneously.
This abstract and the presentation materials are available to members only; a login is required.