7 papers
Utilizing a digital swarm intelligence platform to improve consensus among radiologists and exploring its applications
Rutwik Shah, Bruno Astuto, Tyler Gleason +10
Radiologists today play a key role in making diagnostic decisions and labeling images for training A.I. algorithms. Low inter-reader reliability (IRR) can be seen between experts w…
The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset
Arjun D. Desai, Francesco Caliva, Claudia Iriondo +26
Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthriti…
Hierarchical Severity Staging of Anterior Cruciate Ligament Injuries using Deep Learning with MRI Images
Nikan K. Namiri, Io Flament, Bruno Astuto +6
Purpose: To evaluate the diagnostic utility of two convolutional neural networks (CNNs) for severity staging of anterior cruciate ligament (ACL) injuries. Materials and Methods: Th…
Deep learning predicts total knee replacement from magnetic resonance images
Aniket A. Tolpadi, Jinhee J. Lee, Valentina Pedoia +1
Knee Osteoarthritis (OA) is a common musculoskeletal disorder in the United States. When diagnosed at early stages, lifestyle interventions such as exercise and weight loss can slo…
Automatic Hip Fracture Identification and Functional Subclassification with Deep Learning
Justin D Krogue, Kaiyang V Cheng, Kevin M Hwang +13
Purpose: Hip fractures are a common cause of morbidity and mortality. Automatic identification and classification of hip fractures using deep learning may improve outcomes by reduc…
Adversarial Policy Gradient for Deep Learning Image Augmentation
Kaiyang Cheng, Claudia Iriondo, Francesco Calivá +3
The use of semantic segmentation for masking and cropping input images has proven to be a significant aid in medical imaging classification tasks by decreasing the noise and varian…