collaborators

8 papers

cs.CV2026

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…

cs.CV2026

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…

q-bio.TO2025

Unsupervised whole-heart function assessment

Yundi Zhang, Daniel Rueckert, Jiazhen Pan

Motivation: CMR is the golden standard for cardiac diagnosis, and medical data annotation is time-consuming. Thus, screening techniques from unlabeled data can help streamline the…

eess.IV2025

Reconstruction-free segmentation from undersampled k-space using transformers

Yundi Zhang, Nil Stolt-Ansó, Jiazhen Pan +3

Motivation: High acceleration factors place a limit on MRI image reconstruction. This limit is extended to segmentation models when treating these as subsequent independent process…

cs.CV2025

Does DINOv3 Set a New Medical Vision Standard? Benchmarking 2D and 3D Classification, Segmentation, and Registration

Che Liu, Yinda Chen, Haoyuan Shi +21

The advent of large-scale vision foundation models, pre-trained on diverse natural images, has marked a paradigm shift in computer vision. However, how the frontier vision foundati…

cs.CV2025

Whole-body Representation Learning For Competing Preclinical Disease Risk Assessment

Dmitrii Seletkov, Sophie Starck, Ayhan Can Erdur +3

Reliable preclinical disease risk assessment is essential to move public healthcare from reactive treatment to proactive identification and prevention. However, image-based risk pr…