7 citations · 11 across the 10 of their papers we have counts for
10 papers
Uncertainty-Aware 3D Residual Wavelet Diffusion for Ultra Low-Field MRI Super-Resolution
Rui W. Yeow, Millie Beament, Fred Dick +6
Ultra low-field MRI expands global access to neuroimaging but produces scans with low signal-to-noise ratio, reduced contrast, and thick slices. While regression-based super-resolu…
MPFlow: Multi-modal Posterior-Guided Flow Matching for Zero-Shot MRI Reconstruction
Seunghoi Kim, Chen Jin, Henry F. J. Tregidgo +2
Zero-shot MRI reconstruction relies on generative priors, but single-modality unconditional priors produce hallucinations under severe ill-posedness. In many clinical workflows, co…
HalluGen: Synthesizing Realistic and Controllable Hallucinations for Evaluating Image Restoration
Seunghoi Kim, Henry F. J. Tregidgo, Chen Jin +2
Generative models are prone to hallucinations: plausible but incorrect structures absent in the ground truth. This issue is problematic in image restoration for safety-critical dom…
Connectomics Informed by Large Language Models
Elinor Thompson, Tiantian He, Anna Schroder +5
Tractography is a unique method for mapping white matter connections in the brain, but tractography algorithms suffer from an inherent trade-off between sensitivity and specificity…
Tackling Hallucination from Conditional Models for Medical Image Reconstruction with DynamicDPS
Seunghoi Kim, Henry F. J. Tregidgo, Matteo Figini +3
Hallucinations are spurious structures not present in the ground truth, posing a critical challenge in medical image reconstruction, especially for data-driven conditional models.…
Image Quality Transfer of Diffusion MRI Guided By High-Resolution Structural MRI
Alp G. Cicimen, Henry F. J. Tregidgo, Matteo Figini +7
Prior work on the Image Quality Transfer on Diffusion MRI (dMRI) has shown significant improvement over traditional interpolation methods. However, the difficulty in obtaining ultr…
Tackling Structural Hallucination in Image Translation with Local Diffusion
Seunghoi Kim, Chen Jin, Tom Diethe +5
Recent developments in diffusion models have advanced conditioned image generation, yet they struggle with reconstructing out-of-distribution (OOD) images, such as unseen tumors in…
A 3D Conditional Diffusion Model for Image Quality Transfer -- An Application to Low-Field MRI
Seunghoi Kim, Henry F. J. Tregidgo, Ahmed K. Eldaly +2
Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply. However, they often yield images with lower spatial resolution…
Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI
Henry F. J. Tregidgo, Sonja Soskic, Mark D. Olchanyi +9
The human thalamus is a highly connected subcortical grey-matter structure within the brain. It comprises dozens of nuclei with different function and connectivity, which are affec…
3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology
Henry Tregidgo, Adria Casamitjana, Caitlin Latimer +9
Neuroimaging to neuropathology correlation (NTNC) promises to enable the transfer of microscopic signatures of pathology to in vivo imaging with MRI, ultimately enhancing clinical…