17 citations · 18 across the 6 of their papers we have counts for
6 papers · 1 filter
Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning
Jeffrey Dominic, Nandita Bhaskhar, Arjun D. Desai +8
Although supervised learning has enabled high performance for image segmentation, it requires a large amount of labeled training data, which can be difficult to obtain in the medic…
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation
Arjun D Desai, Andrew M Schmidt, Elka B Rubin +9
Magnetic resonance imaging (MRI) is a cornerstone of modern medical imaging. However, long image acquisition times, the need for qualitative expert analysis, and the lack of (and d…
Rigid and non-rigid motion compensation in weight-bearing cone-beam CT of the knee using (noisy) inertial measurements
Jennifer Maier, Marlies Nitschke, Jang-Hwan Choi +4
Involuntary subject motion is the main source of artifacts in weight-bearing cone-beam CT of the knee. To achieve image quality for clinical diagnosis, the motion needs to be compe…
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…
Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-beam CT
Jennifer Maier, Luis Carlos Rivera Monroy, Christopher Syben +7
Analyzing knee cartilage thickness and strain under load can help to further the understanding of the effects of diseases like Osteoarthritis. A precise segmentation of the cartila…
Technical Considerations for Semantic Segmentation in MRI using Convolutional Neural Networks
Arjun D. Desai, Garry E. Gold, Brian A. Hargreaves +1
High-fidelity semantic segmentation of magnetic resonance volumes is critical for estimating tissue morphometry and relaxation parameters in both clinical and research applications…