2 citations · 3 across the 4 of their papers we have counts for
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ReDiff: Reliability-Guided Diffusion for Trustworthy Ultra-Low-Field to High-Field MRI Synthesis
Zhenxuan Zhang, Peiyuan Jing, Ruicheng Yuan +9
Low-field to high-field MRI synthesis has emerged as a promising strategy to improve image quality when access to high-field scanners is limited. However, in ultra-low-field settin…
Cyclic Self-Supervised Diffusion for Ultra Low-field to High-field MRI Synthesis
Zhenxuan Zhang, Peiyuan Jing, Zi Wang +12
Synthesizing high-quality images from low-field MRI holds significant potential. Low-field MRI is cheaper, more accessible, and safer, but suffers from low resolution and poor sign…
Deep kernel representations of latent space features for low-dose PET-MR imaging robust to variable dose reduction
Cameron Dennis Pain, Yasmeen George, Alex Fornito +2
Low-dose positron emission tomography (PET) image reconstruction methods have potential to significantly improve PET as an imaging modality. Deep learning provides a promising mean…
Perivascular space Identification Nnunet for Generalised Usage (PINGU)
Benjamin Sinclair, Lucy Vivash, Jasmine Moses +16
Perivascular spaces(PVSs) form a central component of the brainś waste clearance system, the glymphatic system. These structures are visible on MRI images, and their morphology is…