Deep learning-based automated detection and segmentation of bone and traumatic bone marrow lesions from MRI following an acute ACL tear.

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第一作者： Callie E,Stirling

第一单位： Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Canada; McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

作者： Callie E,Stirling ^[1] ; Nathan J,Neeteson ^[1] ; Richard E A,Walker ^[2] ; Steven K,Boyd ^[3]

作者单位： Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Canada; McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada. ^[1] McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. ^[2] Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Canada; McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. Electronic address: skboyd@ucalgary.ca. ^[3]

关键词 3D U-Net model Anterior cruciate ligament (ACL) tear Automated segmentation Deep learning (DL)Knee osteoarthritis (OA)Magnetic resonance imaging (MRI)Multi-task learning Traumatic bone marrow lesions (BML)

主题词人类(Humans);磁共振成像(Magnetic Resonance Imaging);骨髓(Bone Marrow);男(雄)性(Male);女(雌)性(Female);成年人(Adult);图像解释, 计算机辅助(Image Interpretation, Computer-Assisted)

DOI 10.1016/j.compbiomed.2024.108791

PMID 38905892

发布时间 2024-07-23

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