Anatomy-Guided Residual Motion Diffusion for Controllable 4D Cardiac MRI Synthesis
Developing robust artificial intelligence models for 4D (3D + time) medical imaging is constrained by limited annotated data, inter-device domain shifts, and privacy restrictions. To address this, we propose a 4D controllable generative framework for anatomically consistent data augmentation. A semi-supervised variational autoencoder learns a compact latent representation of anatomical volumes while jointly predicting aligned segmentation masks in a unified framework. Anatomical structure is the
Record details
Published: 25 June 2026
Source: arXiv
Category: Research
Topics: Privacy · Healthcare
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Evidence-Based Text-Conditioned 3D CT Synthesis for Ovarian Cancer
arXiv · 27 June 2026
Privacy-preserving federated tensor decomposition of single-cell immune data: recovering multicellular programs across institutions
arXiv · 22 June 2026
Recent advances in AI-based mobile robots for human companionship: survey
Artificial Intelligence Review · 29 June 2026
Comparative Analysis of Machine Learning based Intrusion Detection in Realistic IoT Networks
arXiv cs.CR (AI security) · 30 June 2026
"The New Era of Tech-Enabled Traceability": Tensions between the FDA's Data Governance Vision and the Lived Realities of Food Producers
arXiv · 17 June 2026
Mental Health Disorder Detection Beyond Social Media: A Systematic Review of Available Datasets
arXiv cs.CL (ethics-relevant NLP) · 3 July 2026
How to cite this record
ethics.ai (25 June 2026), “Anatomy-Guided Residual Motion Diffusion for Controllable 4D Cardiac MRI Synthesis,” evidence record 575, https://ethics.ai/record/575 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.