151 citations · 599 across the 15 of their papers we have counts for
16 papers
The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff +111
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is mean…
The benefits of prefetching for large-scale cloud-based neuroimaging analysis workflows
Valerie Hayot-Sasson, Tristan Glatard, Ariel Rokem
To support the growing demands of neuroscience applications, researchers are transitioning to cloud computing for its scalable, robust and elastic infrastructure. Nevertheless, lar…
Fractional ridge regression: a fast, interpretable reparameterization of ridge regression
Ariel Rokem, Kendrick Kay
Ridge regression (RR) is a regularization technique that penalizes the L2-norm of the coefficients in linear regression. One of the challenges of using RR is the need to set a hype…
Fitting IVIM with Variable Projection and Simplicial Optimization
Shreyas Fadnavis, Hamza Farooq, Maryam Afzali +10
Fitting multi-exponential models to Diffusion MRI (dMRI) data has always been challenging due to various underlying complexities. In this work, we introduce a novel and robust fitt…
Forecasting Future Humphrey Visual Fields Using Deep Learning
Joanne C. Wen, Cecilia S. Lee, Pearse A. Keane +5
Purpose: To determine if deep learning networks could be trained to forecast a future 24-2 Humphrey Visual Field (HVF). Participants: All patients who obtained a HVF 24-2 at the Un…
Generating retinal flow maps from structural optical coherence tomography with artificial intelligence
Cecilia S. Lee, Ariel J. Tyring, Yue Wu +7
Despite significant advances in artificial intelligence (AI) for computer vision, its application in medical imaging has been limited by the burden and limits of expert-generated l…