65 citations · 69 across the 5 of their papers we have counts for
7 papers
A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging
Davood Karimi, Lana Vasung, Camilo Jaimes +4
Multi-compartment modeling of diffusion-weighted magnetic resonance imaging measurements is necessary for accurate brain connectivity analysis. Existing methods for estimating the…
ODE-based Deep Network for MRI Reconstruction
Ali Pour Yazdanpanah, Onur Afacan, Simon K. Warfield
Fast data acquisition in Magnetic Resonance Imaging (MRI) is vastly in demand and scan time directly depends on the number of acquired k-space samples. The data-driven methods base…
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis
Davood Karimi, Haoran Dou, Simon K. Warfield +1
Supervised training of deep learning models requires large labeled datasets. There is a growing interest in obtaining such datasets for medical image analysis applications. However…
Deep Plug-and-Play Prior for Parallel MRI Reconstruction
Ali Pour Yazdanpanah, Onur Afacan, Simon K. Warfield
Fast data acquisition in Magnetic Resonance Imaging (MRI) is vastly in demand and scan time directly depends on the number of acquired k-space samples. Conventional MRI reconstruct…
Biomechanical modeling and computer simulation of the brain during neurosurgery
K. Miller, G. R. Joldes, G. Bourantas +4
Computational biomechanics of the brain for neurosurgery is an emerging area of research recently gaining in importance and practical applications. This review paper presents the c…
Suite of Meshless Algorithms for Accurate Computation of Soft Tissue Deformation for Surgical Simulation
Grand Joldes, George Bourantas, Benjamin Zwick +7
The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medic…