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.
1 code implementation • 14 Mar 2022 • Arjun D Desai, Andrew M Schmidt, Elka B Rubin, Christopher M Sandino, Marianne S Black, Valentina Mazzoli, Kathryn J Stevens, Robert Boutin, Christopher Ré, Garry E Gold, Brian A Hargreaves, Akshay S Chaudhari
While recent machine learning methods for MRI reconstruction and analysis have shown promise for reducing this burden, these techniques are primarily validated with imperfect image quality metrics, which are discordant with clinically-relevant measures that ultimately hamper clinical deployment and clinician trust.
1 code implementation • 30 Sep 2021 • Arjun D Desai, Batu M Ozturkler, Christopher M Sandino, Robert Boutin, Marc Willis, Shreyas Vasanawala, Brian A Hargreaves, Christopher M Ré, John M Pauly, Akshay S Chaudhari
Deep learning (DL) has shown promise for faster, high quality accelerated MRI reconstruction.