Field-of-View Extension for Diffusion MRI via Deep Generative Models

no code implementations • 6 May 2024 • Chenyu Gao, Shunxing Bao, Michael Kim, Nancy Newlin, Praitayini Kanakaraj, Tianyuan Yao, Gaurav Rudravaram, Yuankai Huo, Daniel Moyer, Kurt Schilling, Walter Kukull, Arthur Toga, Derek Archer, Timothy Hohman, Bennett Landman, Zhiyuan Li

We hypothesize that the imputed image with complete FOV can improve the whole-brain tractography for corrupted data with incomplete FOV.

Imputation

Robust Fiber ODF Estimation Using Deep Constrained Spherical Deconvolution for Diffusion MRI

no code implementations • 5 Jun 2023 • Tianyuan Yao, Francois Rheault, Leon Y Cai, Vishwesh Nath, Zuhayr Asad, Nancy Newlin, Can Cui, Ruining Deng, Karthik Ramadass, Andrea Shafer, Susan Resnick, Kurt Schilling, Bennett A. Landman, Yuankai Huo

From the experimental results, the proposed data-driven framework outperforms the existing benchmarks in repeated fODF estimation.

A Unified Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-weighted MRI

no code implementations • 29 Mar 2023 • Tianyuan Yao, Nancy Newlin, Praitayini Kanakaraj, Vishwesh Nath, Leon Y Cai, Karthik Ramadass, Kurt Schilling, Bennett A. Landman, Yuankai Huo

Diffusion-weighted (DW) MRI measures the direction and scale of the local diffusion process in every voxel through its spectrum in q-space, typically acquired in one or more shells.