2 citations · 3 across the 9 of their papers we have counts for
10 papers
Uncertainty-Aware Cortical Surface Reconstruction and Spherical Registration for Heterogeneous Brain MRI
Jesper Duemose Nielsen, Karthik Gopinath, Andrew Hoopes +4
Surface-based cortical analysis is useful in many applications as it is a natural way to model the highly folded structure of the cerebral cortex, allowing quantities such as curva…
JParc: Joint cortical surface parcellation with registration
Jian Li, Karthik Gopinath, Brian L. Edlow +2
Cortical surface parcellation is a fundamental task in both basic neuroscience research and clinical applications, enabling more accurate mapping of brain regions. Model-based and…
A Modality-agnostic Multi-task Foundation Model for Human Brain Imaging
Peirong Liu, Oula Puonti, Xiaoling Hu +5
Recent learning-based approaches have made astonishing advances in calibrated medical imaging like computerized tomography (CT), yet they struggle to generalize in uncalibrated mod…
Automated Segmentation of Coronal Brain Tissue Slabs for 3D Neuropathology
Jonathan Williams Ramirez, Dina Zemlyanker, Lucas Deden-Binder +15
Advances in image registration and machine learning have recently enabled volumetric analysis of postmortem brain tissue from conventional photographs of coronal slabs, which are r…
UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs
Raghav Mehta, Karthik Gopinath, Ben Glocker +1
We propose UNSURF, a novel uncertainty measure for cortical surface reconstruction of clinical brain MRI scans of any orientation, resolution, and contrast. It relies on the discre…
End-to-end Cortical Surface Reconstruction from Clinical Magnetic Resonance Images
Jesper Duemose Nielsen, Karthik Gopinath, Andrew Hoopes +7
Surface-based cortical analysis is valuable for a variety of neuroimaging tasks, such as spatial normalization, parcellation, and gray matter (GM) thickness estimation. However, mo…
From Low Field to High Value: Robust Cortical Mapping from Low-Field MRI
Karthik Gopinath, Annabel Sorby-Adams, Jonathan W. Ramirez +12
Three-dimensional reconstruction of cortical surfaces from MRI for morphometric analysis is fundamental for understanding brain structure. While high-field MRI (HF-MRI) is standard…
Hierarchical Uncertainty Estimation for Learning-based Registration in Neuroimaging
Xiaoling Hu, Karthik Gopinath, Peirong Liu +4
Over recent years, deep learning based image registration has achieved impressive accuracy in many domains, including medical imaging and, specifically, human neuroimaging with mag…
Recon-all-clinical: Cortical surface reconstruction and analysis of heterogeneous clinical brain MRI
Karthik Gopinath, Douglas N. Greve, Colin Magdamo +4
Surface-based analysis of the cerebral cortex is ubiquitous in human neuroimaging with MRI. It is crucial for cortical registration, parcellation, and thickness estimation. Traditi…
Registration by Regression (RbR): a framework for interpretable and flexible atlas registration
Karthik Gopinath, Xiaoling Hu, Malte Hoffmann +2
In human neuroimaging studies, atlas registration enables mapping MRI scans to a common coordinate frame, which is necessary to aggregate data from multiple subjects. Machine learn…