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Quantifying Prediction Uncertainty in Kidney Tumor Segmentation Using a Guided Decoder Attention U-Net

2026-06-23

Abstract excerpt

<title>Abstract</title> <p>In modern oncology, accurate segmentation of kidney tumors on CT images supports diagnosis, surgical planning, and treatment evaluation. We proposed an automatic segmentation method for kidney tumors and cysts based on the Guided Decoder (ARU-GD) using Attention Residual UNet. The guided decoder uses multi-scale features and progressively refined stage-wise loss functions. Attention gat...

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Literature Corpus work: 80558d51-f45e-5397-af3f-1c50463f9438
DOI: 10.21203/rs.3.rs-10021018/v1

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