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HCC Segmentation and Differentiation Model by Jack H is a document available to read on EtoBox.

What is HCC Segmentation and Differentiation Model about?

This paper proposes a multi-task learning model for hepatocellular carcinoma (HCC) segmentation and prediction of pathological differentiation degree. The model consists of a segmentation subnet and a classification subnet. The segmentation subnet uses boundary-aware attention to address tumor over-segmentation, while the classification subnet employs multi-scale feature fusion to improve classification accuracy. Experimental results on 295 HCC patients show the model achieves superior performance compared

Author
Jack H
Language
EN