74 citations · 538 across the 71 of their papers we have counts for
41 papers · 1 filter
A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images
Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit +7
Quantifying the perceptual similarity of two images is a long-standing problem in low-level computer vision. The natural image domain commonly relies on supervised learning, e.g.,…
Artificial Intelligence-Based Image Reconstruction in Cardiac Magnetic Resonance
Chen Qin, Daniel Rueckert
Artificial intelligence (AI) and Machine Learning (ML) have shown great potential in improving the medical imaging workflow, from image acquisition and reconstruction to disease di…
Review of data types and model dimensionality for cardiac DTI SMS-related artefact removal
Michael Tanzer, Sea Hee Yook, Guang Yang +2
As diffusion tensor imaging (DTI) gains popularity in cardiac imaging due to its unique ability to non-invasively assess the cardiac microstructure, deep learning-based Artificial…
Learning-based and unrolled motion-compensated reconstruction for cardiac MR CINE imaging
Jiazhen Pan, Daniel Rueckert, Thomas Küstner +1
Motion-compensated MR reconstruction (MCMR) is a powerful concept with considerable potential, consisting of two coupled sub-problems: Motion estimation, assuming a known image, an…
Mesh-based 3D Motion Tracking in Cardiac MRI using Deep Learning
Qingjie Meng, Wenjia Bai, Tianrui Liu +2
3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and diagnosis of cardiovascular diseases. Most of the pre…
FedNorm: Modality-Based Normalization in Federated Learning for Multi-Modal Liver Segmentation
Tobias Bernecker, Annette Peters, Christopher L. Schlett +5
Given the high incidence and effective treatment options for liver diseases, they are of great socioeconomic importance. One of the most common methods for analyzing CT and MRI ima…