activity
20192021
most citedDevelopment of Conditional Random Field Insert for UNet-based Zonal Prostate Segmentation on T2-Weighted MRI

1 citations · 1 across the 5 of their papers we have counts for

collaborators

9 papers

cs.HC2021

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…

eess.IV2020

Adversarial Robust Training of Deep Learning MRI Reconstruction Models

Francesco Calivá, Kaiyang Cheng, Rutwik Shah +1

Deep Learning (DL) has shown potential in accelerating Magnetic Resonance Image acquisition and reconstruction. Nevertheless, there is a dearth of tailored methods to guarantee tha…

eess.IV2020

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…

eess.IV2020

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…

eess.IV2020

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…

q-bio.QM20201 cited

Development of Conditional Random Field Insert for UNet-based Zonal Prostate Segmentation on T2-Weighted MRI

Peng Cao, Susan M. Noworolski, Olga Starobinets +6

Purpose: A conventional 2D UNet convolutional neural network (CNN) architecture may result in ill-defined boundaries in segmentation output. Several studies imposed stronger constr…