4 papers
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…
CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI Reconstruction
Mevan Ekanayake, Zhifeng Chen, Mehrtash Harandi +2
In Magnetic Resonance Imaging (MRI), image acquisitions are often undersampled in the measurement domain to accelerate the scanning process, at the expense of image quality. Howeve…
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…