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The Effect of Activation Functions and Loss Functions on Deep Learning Based Fully Automated Knee Joint Segmentation

Author:Sibaji Gaj  Dennis Chan  Xiaojuan Li  

Session Type:Oral  

Session Date:Thursday, 20 May 2021  

Topic:Artificial Intelligence Applied to MSK MRI  

Session Name:Artificial Intelligence Applied to MSK MRI  

Program Number:0807  

Room Session:Concurrent 4  

Institution:Cleveland Clinic  

Efficient Phase Cycling Strategy for High Resolution Three-Dimensional GRE Quantitative Mapping

Evaluation of Dixon MRI Methods for Quantitative Assessment of Thigh Muscle Fatty Infiltration in Post-Traumatic Osteoarthritis

Feasibility of Femoral Cartilage Lesion Classification on Clinical MRIs using Deep Learning

Author:Mingrui Yang  Ceylan Colak  Mercan Aslan  Sibaji Gaj  Morgan Jones  Carl Winalski  Naveen Subhas  Xiaojuan Li  

Session Type:Digital Poster  

Session Date:Thursday, 20 May 2021  

Topic:Artificial Intelligence Applied to MSK MRI  

Session Name:Artificial Intelligence  

Program Number:4064  

Room Session:Concurrent 4  

Institution:Cleveland Clinic  

Highly accelerated T1? imaging using kernel-based low-rank compressed sensing reconstruction in knees with and without osteoarthritis

The Latest & Greatest: Future

Author:Xiaojuan Li  

Session Type:Sunrise Session  

Session Date:Wednesday, 19 May 2021  

Topic:Hot Topics in MSK MRI  

Session Name:Novel MRI Techniques Applied to Musculoskeletal Diseases  

Program Number:

Room Session:Concurrent 7  

Institution:Cleveland Clinic  

    A Marker Controlled Active Contour Model for Thigh Muscle Segmentation in MR Images

    Author:Weihong Guo  Michael Judkovich  Richard Lartey  Dongxing Xie  Mingrui Yang  Xiaojuan Li  

    Session Type:Digital Poster  

    Session Date:Wednesday, 19 May 2021  

    Topic:Muscle MRI  

    Session Name:Muscle MRI  

    Program Number:3172  

    Room Session:Concurrent 4  

    Institution:Case Western Reserve University  Cleveland Clinic  

    Quantitative MRI in Osteoarthritis: Novel Methods & Their Potential

      SuperMAP: Superfast MR Mapping with Joint Under-sampling using Deep Combined Network