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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019; 22nd International C Dinggang Shen,Tianming Liu,Ali Khan Conferen

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Boundary and Entropy-Driven Adversarial Learning for Fundus Image Segmentationictions of OD and OC segmentation. We evaluate the proposed BEAL framework on two public retinal fundus image datasets (Drishti-GS and RIM-ONE-r3), and the experiment results demonstrate that our method outperforms the state-of-the-art unsupervised domain adaptation methods. Our code is available at ..
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Task Adaptive Metric Space for Medium-Shot Medical Image Classificationesent medical data in a more semantically meaningful way. Our empirical studies suggest that TAMS outperforms other baselines. Visualizations on the metric space show TAMS leads to better-separated clusters. Our baselines and evaluation procedure of the proposed TAMS opens the door to more research on medium-shot medical image classification.
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Georgios Lazaridis,Marco Lorenzi,Sebastien Ourselin,David Garway-Heath
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Gongning Luo,Suyu Dong,Kuanquan Wang,Dong Zhang,Yue Gao,Xin Chen,Henggui Zhang,Shuo Li
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Ricardo J. Araújo,Jaime S. Cardoso,Hélder P. Oliveira
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Shujun Wang,Lequan Yu,Kang Li,Xin Yang,Chi-Wing Fu,Pheng-Ann Heng
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