5 citations · 9 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolution
Mevan Ekanayake, Zhifeng Chen, Gary Egan +2
Implicit Neural Representations (INRs) have recently advanced the field of deep learning due to their ability to learn continuous representations of signals without the need for la…
Motion-Informed Deep Learning for Brain MR Image Reconstruction Framework
Zhifeng Chen, Kamlesh Pawar, Kh Tohidul Islam +3
Motion artifacts in Magnetic Resonance Imaging (MRI) are one of the frequently occurring artifacts due to patient movements during scanning. Motion is estimated to be present in ap…
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…