Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning

no code implementations • 14 Oct 2022 • Jeffrey Dominic, Nandita Bhaskhar, Arjun D. Desai, Andrew Schmidt, Elka Rubin, Beliz Gunel, Garry E. Gold, Brian A. Hargreaves, Leon Lenchik, Robert Boutin, Akshay S. Chaudhari

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 medical imaging field.

Image Segmentation Segmentation +2

SSFD: Self-Supervised Feature Distance as an MR Image Reconstruction Quality Metric

no code implementations • NeurIPS Workshop Deep_Invers 2021 • Philip M Adamson, Beliz Gunel, Jeffrey Dominic, Arjun D Desai, Daniel Spielman, Shreyas Vasanawala, John M. Pauly, Akshay Chaudhari

Self-supervised learning (SSL) has become a popular pre-training tool due to its ability to capture generalizable and domain-specific feature representations of the underlying data for downstream tasks.

MRI Reconstruction Self-Supervised Learning +1