13 citations · 38 across the 30 of their papers we have counts for
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CMRVision: A Foundation Model for Cardiac MR Image Analysis
Athira J. Jacob, Puneet Sharma, Daniel Rueckert
Cardiac magnetic resonance (CMR) imaging provides complementary information on cardiac anatomy, function, and tissue characterization across multiple sequences and views. In this w…
MR-JEPA: A General Purpose Video Foundation Model for Cardiac MRI
Athira J. Jacob, Puneet Sharma, Dorin Comaniciu +1
Cardiac magnetic resonance imaging (CMR) produces rich sequential data such as temporal cine videos and spatial LGE/mapping stacks, yet most deep learning approaches process indivi…
Primitive Representation Learning for Unsupervised Dynamic Contrast Enhanced MRI Reconstruction
Veronika Spieker, Wenqi Huang, Cemre Ariyurek +5
Reliable quantitative analysis of dynamic contrast-enhanced MRI requires high-quality spatiotemporal reconstructions at high undersampling rates. Scan-specific reconstructions usin…
Distortion-Corrected Diffusion MRI Using Rotated-View EPI and Joint Field-Map/Image Estimation with Gaussian Primitives
Wenqi Huang, Zhitao Li, Nan Wang +8
Echo Planar Imaging (EPI) is the standard acquisition technique for diffusion and functional neuroimaging, enabling rapid imaging but suffering from geometric distortions caused by…
Cross-Modal Contrastive Learning of ECG and Angiography Representations for Severe Stenosis Classification
Nikola Cenikj, Özgün Turgut, Alexander Müller +5
Coronary artery stenosis is a common cardiovascular disease, with severe, untreated cases posing significant risks of heart attack. Although coronary (X-ray) angiograms remain the…
LGESynthNet: Controlled Scar Synthesis for Improved Scar Segmentation in Cardiac LGE-MRI Imaging
Athira J. Jacob, Puneet Sharma, Daniel Rueckert
Segmentation of enhancement in LGE cardiac MRI is critical for diagnosing various ischemic and non-ischemic cardiomyopathies. However, creating pixel-level annotations for these im…
Opportunistic Cardiac Health Assessment: Estimating Phenotypes from Localizer MRI through Multi-Modal Representations
Busra Nur Zeybek, Özgün Turgut, Yundi Zhang +5
Cardiovascular diseases are the leading cause of death. Cardiac phenotypes (CPs), e.g., ejection fraction, are the gold standard for assessing cardiac health, but they are derived…
No Image, No Problem: End-to-End Multi-Task Cardiac Analysis from Undersampled k-Space
Yundi Zhang, Sevgi Gokce Kafali, Niklas Bubeck +2
Conventional clinical CMR pipelines rely on a sequential "reconstruct-then-analyze" paradigm, forcing an ill-posed intermediate step that introduces avoidable artifacts and informa…
Gabor Primitives for Accelerated Cardiac Cine MRI Reconstruction
Wenqi Huang, Veronika Spieker, Nil Stolt-Ansó +6
Accelerated cardiac cine MRI requires reconstructing spatiotemporal images from highly undersampled k-space data. Implicit neural representations (INRs) enable scan-specific recons…
Echo2ECG: Enhancing ECG Representations with Cardiac Morphology from Multi-View Echos
Michelle Espranita Liman, Özgün Turgut, Alexander Müller +3
Electrocardiography (ECG) is a low-cost, widely used modality for diagnosing electrical abnormalities like atrial fibrillation by capturing the heart's electrical activity. However…
Stroke outcome and evolution prediction from CT brain using a spatiotemporal diffusion autoencoder
Adam Marcus, Paul Bentley, Daniel Rueckert
Stroke is a major cause of death and disability worldwide. Accurate outcome and evolution prediction has the potential to revolutionize stroke care by individualizing clinical deci…
Towards a Unified Theoretical Framework for Splitting-based Self-Supervised MRI Reconstruction
Siying Xu, Kerstin Hammernik, Daniel Rueckert +2
The demand for high-resolution, non-invasive imaging continues to drive innovation in magnetic resonance imaging (MRI), but long acquisition times remain a major practical limitati…