1 code implementation • 31 Mar 2021 • Shuo Han, Samuel Remedios, Aaron Carass, Michael Schär, Jerry L. Prince
To super-resolve the through-plane direction of a multi-slice 2D magnetic resonance (MR) image, its slice selection profile can be used as the degeneration model from high resolution (HR) to low resolution (LR) to create paired data when training a supervised algorithm.
no code implementations • 11 Mar 2019 • Samuel Remedios, Snehashis Roy, Justin Blaber, Camilo Bermudez, Vishwesh Nath, Mayur B. Patel, John A. Butman, Bennett A. Landman, Dzung L. Pham
Machine learning models are becoming commonplace in the domain of medical imaging, and with these methods comes an ever-increasing need for more data.
no code implementations • 9 Oct 2018 • Vishwesh Nath, Prasanna Parvathaneni, Colin B. Hansen, Allison E. Hainline, Camilo Bermudez, Samuel Remedios, Justin A. Blaber, Kurt G. Schilling, Ilwoo Lyu, Vaibhav Janve, Yurui Gao, Iwona Stepniewska, Baxter P. Rogers, Allen T. Newton, L. Taylor Davis, Jeff Luci, Adam W. Anderson, Bennett A. Landman
Herein, we propose a data-driven tech-nique using a neural network design which exploits two categories of data.
no code implementations • 16 Apr 2018 • Samuel Remedios, Dzung L. Pham, John A. Butman, Snehashis Roy
The proposed CNN automatically identifies the MR contrast of an input brain image volume.