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Deep-learning Methods for Meniscus Segmentation in Knee MRI

Author:Siyue Li  Shutian Zhao  Sheheryark Khan  Weitian Chen  

Institution:CUHK lab of AI in radiology (CLAIR), The Chinese University of Hong Kong  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:Machine Learning and Emerging Methods in MSK  

Session Name:Machine Learning in Musculoskeletal 1  

Program Number:2650  

Room Live Q&A Session:

Fully Automatic Multi-label Segmentation of Knee joint MRI using Deep Learning Neural Networks

Author:Siyue Li  Xiaorui Xu  Chun Ki Franklin Au  Weitian Chen  

Institution:CUHK lab of AI in radiology (CLAIR), Department of imaging and interventional radiology , The Chinese University of Hong Kong  Department of imaging and interventional radiology, The Chinese University of Hong Kong  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:Machine Learning and Emerging Methods in MSK  

Session Name:Musculoskeletal Emerging Methods/Machine Learning 2  

Program Number:2665  

Room Live Q&A Session:

Noise Reduction of 3D Fast Spin Echo Knee Imaging Using Fusion of Convolutional Neural Networks

Author:Shutian Zhao  Siyue Li  Xiaorui Xu  Chun Ki Franklin Au  Huimin Zhang  Weitian Chen  

Institution:CUHK lab of AI in radiology (CLAIR), Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:Machine Learning and Emerging Methods in MSK  

Session Name:Machine Learning in Musculoskeletal 1  

Program Number:2662  

Room Live Q&A Session:

Perceptual Noise-Estimation based Method for MRI denoising with deep learning

Author:Xiaorui Xu  Siyue Li  Shutian Zhao  Chun Ki Franklin Au  Weitian Chen  

Institution:The Chinese University of Hong Kong  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:Software Tools and Image Analysis  

Session Name:Image Analysis 2  

Program Number:3676  

Room Live Q&A Session: