TP2.L302: Biomedical Image Segmentation
Tue, 10 Oct, 16:30 - 18:00 Malaysia Time (UTC +8)
Location: Room 302
Session Type: Lecture
Session Chair: Benoit Macq, UCLouvain
Track: Applications of Machine Learning
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Tue, 10 Oct, 16:30 - 16:48 Malaysia Time (UTC +8)
 

TP2.L302.1: SEMI-SUPERVISED CONTRASTIVE LEARNING OF GLOBAL AND LOCAL REPRESENTATION FOR 3D MEDICAL IMAGE SEGMENTATION
Chuang Jia, Jian Xue, Ke Lu, Zhongqi Wu, University of Chinese Academy of Sciences, China
Tue, 10 Oct, 16:48 - 17:06 Malaysia Time (UTC +8)
 

TP2.L302.2: SELF-REINFORCING FOR FEW-SHOT MEDICAL IMAGE SEGMENTATION
Yao Huang, Jianming Liu, Hua Chen, Jiangxi Normal University, China
Tue, 10 Oct, 17:06 - 17:24 Malaysia Time (UTC +8)
 

TP2.L302.3: Densely Connected Swin-UNet for Multiscale Information Aggregation in Medical Image Segmentation
Ziyang Wang, Oxford University, United Kingdom of Great Britain and Northern Ireland; Meiwen Su, University of Hong Kong, China; Jian-Qing Zheng, Oxford University, United Kingdom of Great Britain and Northern Ireland; Yang Liu, University of Plymouth, United Kingdom of Great Britain and Northern Ireland
Tue, 10 Oct, 17:24 - 17:42 Malaysia Time (UTC +8)
 

TP2.L302.4: SEGMENTATION AND CLASSIFICATION-BASED DIAGNOSIS OF TUMORS FROM BREAST ULTRASOUND IMAGES USING MULTIBRANCH UNET
Laksath Adityan M K, Himanchal Sharma, Angshuman Paul, Indian Institute of Technology Jodhpur, India
Tue, 10 Oct, 17:42 - 18:00 Malaysia Time (UTC +8)
 

TP2.L302.5: LEARNABLE SNAKE R-CNN FOR INSTANCE-LEVEL BIOMEDICAL IMAGE SEGMENTATION
Jie Song, Ziyun Cai, Yurong Song, Guoping Jiang, Nanjing University of Posts and Telecommunications, China; Zhichao Lian, Liang Xiao, Nanjing University of Science and Technology, China