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ORCID1st REMIA@MICCAI 2022: Singapore
- Xinxing Xu
, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Huazhu Fu:
Resource-Efficient Medical Image Analysis - First MICCAI Workshop, REMIA 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13543, Springer 2022, ISBN 978-3-031-16875-8 - Rudan Xiao, Damien Ambrosetti, Xavier Descombes:
Multi-task Semi-supervised Learning for Vascular Network Segmentation and Renal Cell Carcinoma Classification. 1-11 - Hanyun Zhang, Khalid AbdulJabbar, Tami Grunewald, Ayse U. Akarca, Yeman Brhane Hagos, Catherine S. Y. Lecat, Dominic Patel, Lydia Lee, Manuel Rodriguez-Justo, Kwee Yong, Jonathan A. Ledermann, John Le Quesne, Teresa Marafioti, Yinyin Yuan:
Self-supervised Antigen Detection Artificial Intelligence (SANDI). 12-21 - Keegan Quigley, Miriam Cha, Ruizhi Liao, Geeticka Chauhan, Steven Horng, Seth J. Berkowitz, Polina Golland:
RadTex: Learning Efficient Radiograph Representations from Text Reports. 22-31 - Yuexiang Li, Nanjun He, Yawen Huang:
Single Domain Generalization via Spontaneous Amplitude Spectrum Diversification. 32-41 - Ziyang Wang, Irina Voiculescu:
Triple-View Feature Learning for Medical Image Segmentation. 42-54 - Nazanin Beheshti, Lennart Johnsson:
Classification of 4D fMRI Images Using ML, Focusing on Computational and Memory Utilization Efficiency. 55-64 - Linh D. Le, Huazhu Fu, Xinxing Xu, Yong Liu, Yanyu Xu, Jiawei Du, Joey Tianyi Zhou, Rick Siow Mong Goh:
An Efficient Defending Mechanism Against Image Attacking on Medical Image Segmentation Models. 65-74 - Quan Liu, Can Cui, Ruining Deng, Zuhayr Asad, Tianyuan Yao, Zheyu Zhu, Yuankai Huo:
Leverage Supervised and Self-supervised Pretrain Models for Pathological Survival Analysis via a Simple and Low-cost Joint Representation Tuning. 75-84 - Wenkang Qin, Shan Jiang, Lin Luo:
Pathological Image Contrastive Self-supervised Learning. 85-94 - Aliasghar Tarkhan, Trung Kien Nguyen, Noah Simon, Jian Dai:
Investigation of Training Multiple Instance Learning Networks with Instance Sampling. 95-104 - Zehui Lin, Ruobing Huang, Dong Ni, Jiayi Wu, Baoming Luo:
Masked Video Modeling with Correlation-Aware Contrastive Learning for Breast Cancer Diagnosis in Ultrasound. 105-114 - Achraf Ouahab, Olfa Ben Ahmed, Christine Fernandez-Maloigne:
A Self-attentive Meta-learning Approach for Image-Based Few-Shot Disease Detection. 115-125 - Yanyu Xu, Xinxing Xu, Huazhu Fu, Meng Wang, Rick Siow Mong Goh, Yong Liu:
Facing Annotation Redundancy: OCT Layer Segmentation with only 10 Annotated Pixels per Layer. 126-136
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