21 citations · 122 across the 20 of their papers we have counts for
6 papers · 1 filter
Spatially Covariant Image Registration with Text Prompts
Xiang Chen, Min Liu, Rongguang Wang +4
Medical images are often characterized by their structured anatomical representations and spatially inhomogeneous contrasts. Leveraging anatomical priors in neural networks can gre…
DAGrid: Directed Accumulator Grid
Hang Zhang, Renjiu Hu, Xiang Chen +3
Recent research highlights that the Directed Accumulator (DA), through its parametrization of geometric priors into neural networks, has notably improved the performance of medical…
High-pass filtered fidelity-imposed network edit (HP-FINE) for robust quantitative susceptibility mapping from high-pass filtered phase
Jinwei Zhang, Alexey Dimov, Chao Li +4
Purpose: To improve the generalization ability of deep learning based predictions of quantitative susceptibility mapping (QSM) from high-pass filtered phase (HPFP) data. Methods: A…
mcLARO: Multi-Contrast Learned Acquisition and Reconstruction Optimization for simultaneous quantitative multi-parametric mapping
Jinwei Zhang, Thanh D. Nguyen, Eddy Solomon +6
Purpose: To develop a method for rapid sub-millimeter T1, T2, T2* and QSM mapping in a single scan using multi-contrast Learned Acquisition and Reconstruction Optimization (mcLARO)…
DeDA: Deep Directed Accumulator
Hang Zhang, Rongguang Wang, Renjiu Hu +2
Chronic active multiple sclerosis lesions, also termed as rim+ lesions, can be characterized by a hyperintense rim at the edge of the lesion on quantitative susceptibility maps. Th…
Spatially Covariant Lesion Segmentation
Hang Zhang, Rongguang Wang, Jinwei Zhang +3
Compared to natural images, medical images usually show stronger visual patterns and therefore this adds flexibility and elasticity to resource-limited clinical applications by inj…