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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2021; 24th International C Marleen de Bruijne,Philippe C. Cattin,Caroli

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mfTrans-Net: Quantitative Measurement of Hepatocellular Carcinoma via Multi-Function Transformer Reg Transformer captures the relevance between multi-phase CEMRI for multi-phase CEMRI information fusion and selection. Lastly, we proposed a multi-level training strategy, which enables an enhanced loss function to improve the quantification task. The mfTrans-Net is validated on multi-phase CEMRI of
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A Coherent Cooperative Learning Framework Based on Transfer Learning for Unsupervised Cross-Domain Cted in turn, and the data is transferred between different modules to realize the knowledge transfer and collaborative training. The final prediction is obtained by a voting result of two classifiers. Experimental results on three pneumonia databases demonstrate the effectiveness of our framework wi
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