arXiv:2610.09185v1 Announce Type: new
Abstract: Cine cardiovascular magnetic resonance (CMR) captures the cardiac cycle as a four-dimensional (4D) sequence, but standard acquisition requires electroc...
By Shiyi Wang, Ruochen Sun, Xiang Li, Peirong Liu, Fangxu Xing
The paper introduces a self‑supervised method for detecting end‑diastole (ED) and end‑systole (ES) in echocardiography by constraining the latent motion to a single‑parameter orbit, effectively modeling cardiac phase as a one‑dimensional signal. This approach yields an interpretable representation that directly identifies ED and ES, improving ED localisation and matching ES performance compared to prior state‑of‑the‑art methods, while using fewer training epochs and a more constrained model. The method is trained on EchoNet‑Dynamic without annotations and the code is publicly available.
By John Bonnici, Matthew Baugh, Aleksandra Kulbaka, Sarah Cechnicka, Bernhard Kainz, Alberto Gomez
arXiv:2606. 26718v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular structure and motion, but conventional risk models use only a few image-derived indices from selected cardiac phases.
By David Br\"uggemann, Ekaterina Krymova, Firat \"Ozdemir, Jochen von Spiczak, Sebastian Kozerke, Samia Mora, Robert Manka, Mathieu Salzmann, Olga V. Demler
arXiv:2608.24027v1 Announce Type: new
Abstract: 4D medical image interpolation aims to recover missing volumes from sparsely observed time points and is important for dynamic anatomical analysis in a...
By Haojin Li, Hengzhuo Wang, Zhiheng Ma, Mingyang Ou, Heng Li, Jiang Liu
arXiv:2608. 19738v1 Announce Type: cross Abstract: Full-cycle biventricular geometry is essential for characterizing cardiac function.
By Xuan Yang, Xiaohan Yuan, Hao Li, Lingyu Chen, Yanan Liu, Qingya Li, Lei Li
arXiv:2606. 14759v1 Announce Type: cross Abstract: Cine cardiac magnetic resonance is the gold standard for assessing cardiac function, but the scarcity of public datasets limits the development of advanced data-driven models.
By Yiheng Cao (SyCoIA - IMT Mines Al\`es), Gustavo Andrade-Miranda (SyCoIA - IMT Mines Al\`es), Jiatian Zhang, Guillaume Sall\'e, Xin Gao
The paper introduces cylindrical geodesic flow matching, a method for translating quasiperiodic cardiovascular waveforms between different body locations. By replacing the standard affine path in flow matching with a closed‑form geodesic on a phase–amplitude cylinder, the approach preserves amplitude and instantaneous frequency during interpolation. Experiments on photoplethysmography and seismocardiography data show that this geometry‑aware method outperforms interpolation baselines and matches or exceeds supervised models, reducing error metrics by up to ~15%.
By Onur Selim Kilic, Afra Nawar, Cem Okan Yaldiz, Michael J. Cho, Ahmet Rasim Emirdagi, Demet Tangolar, Amirali Aghazadeh, Amit J. Shah, Omer T. Inan
arXiv:2608.28712v1 Announce Type: cross
Abstract: Objective: Clinical cardiac CT multiphase reconstructions generally provide acceptable image quality in end-diastole (ED) or end-systole (ES) phases,...
By Yuang Wang, Shuo Wang, Changyu Chen, Dufan Wu, Pengfei Jin, Yunqiang An, Yang Gao, Bin Lu, Dongrui Dai, Muge Du, Yan Yan, Dong Li, Liang Li, Li Zhang, Zhiqiang Chen
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.
arXiv:2607. 09805v1 Announce Type: cross Abstract: Percutaneous Coronary Intervention (PCI) is a minimally invasive procedure used to restore coronary blood flow obstructed by atherosclerotic plaque.
By Saahil Islam, Sebastian Piat, Venkatesh N. Murthy, Serkan Cimen, Puneet Sharma, Andreas Maier, Florin C. Ghesu
The paper introduces ORBIT, a self‑supervised method for detecting end‑diastolic and end‑systolic cardiac phases in fetal echocardiography without manual annotations. ORBIT learns a latent motion trajectory through registration, enabling orientation‑robust identification of phase transitions across diverse fetal heart positions. Evaluated on normal and congenital heart disease cases, it achieves low mean absolute errors (≈1.9–2.4 frames) and outperforms prior annotation‑free approaches that assume fixed orientations.
By Yingyu Yang, Qianye Yang, Can Peng, Elena D'Alberti, Olga Patey, Aris T. Papageorghiou, J. Alison Noble
arXiv:2606. 26764v1 Announce Type: cross Abstract: Developing robust artificial intelligence models for 4D (3D + time) medical imaging is constrained by limited annotated data, inter-device domain shifts, and privacy restrictions.
By Yiheng Cao, Gustavo Andrade-Miranda, Jiatian Zhang, Lingxiao Zhao, Xin Gao