Deep Learning for Medical Image Segmentation with Imprecise Annotation

Medical image segmentation (MIS) plays an instrumental role in medical image analysis, where considerable efforts have been devoted to automating the process. Currently, mainstream MIS approaches are based on deep neural networks (DNNs) which are typically trained on a dataset that contains annotation masks produced by doctors. However, in the medical domain, the annotation masks generated by different doctors can inherently vary because a doctor may unnecessarily produce precise and unique annotations to meet the goal of diagnosis. Therefore, the …

analysis annotation cs.cv cs.ne dataset deep learning doctors image masks medical networks neural networks process role segmentation