Progressively Training an Enhanced U-Net Model for Segmentation of Kidney Tumors

XueJian HE, Ping Shun Leung, Lu Wang
2019 Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19   unpublished
An enhanced U-Net model with multi-scale inputs and deep supervision are adopted for Kidney tumor segmentation. Focal Tversky Loss is used to train the model, in order to improve the model performance of detecting small tumors. Progressive training is proposed for facilitating model converge. A simple postprocessing method is used to remove segmentation noises. The preliminary results indicate that the proposed model can segment the normal kidney with a satisfactory result; for the tumors with
more » ... or the tumors with small sizes in low contrast or extreme sizes, there is still a room for improvement.
doi:10.24926/548719.056 fatcat:qaprbndepja3tbs3ot2gyhdsrm