5 citations · 5 across the 4 of their papers we have counts for
4 papers
U-TTT: Towards Generalizable PET Image Denoising via Test-Time Training
Zhiwen Yang, Jiayin Li, Hao Lu +3
Existing deep learning models for Positron Emission Tomography (PET) image denoising often suffer from severe performance degradation under distribution shifts, fundamentally restr…
Quality assessment of brain structural MR images: Comparing generalization of deep learning versus hand-crafted feature-based machine learning methods to new sites
Prabhjot Kaur, John S. Thornton, Frederik Barkhof +3
Quality assessment of brain structural MR images is critical for large-scale neuroimaging studies, where motion artifacts can significantly bias clinical estimates. While visual ra…
Real-time, inline quantitative MRI enabled by scanner-integrated machine learning: a proof of principle with NODDI
Samuel Rot, Iulius Dragonu, Christina Triantafyllou +11
Purpose: The clinical feasibility and translation of many advanced quantitative MRI (qMRI) techniques are inhibited by their restriction to 'research mode', due to resource-intensi…
Decoding Gray Matter: large-scale analysis of brain cell morphometry to inform microstructural modeling of diffusion MR signals
Charlie Aird-Rossiter, Hui Zhang, Daniel C. Alexander +2
The structure of grey matter has long been a key focus in neuroscience, as cell morphology varies by type and can be affected by neurological conditions. Understanding these variat…