arXiv:2608. 03430v1 Announce Type: cross Abstract: Four-dimensional cone beam CT (4D CBCT) is important for image-guided radiation therapy of thoracic cancers, but its use is limited by long scan times, causing high patient dose and motion/sparse-sampling artifacts.
EchoDiST is an unsupervised framework for estimating myocardial motion in echocardiography, combining self‑distillation joint learning of anatomical segmentation and motion estimation with a diffusion‑conditioned network. The method uses limited anatomical annotations and stochastic perturbations during training, yet requires only a single deterministic forward pass at inference. Evaluated on three datasets, EchoDiST consistently outperforms seven other learning‑based approaches in anatomical alignment, strain assessment, and functional metrics, with statistically significant improvements across cross‑view and cross‑dataset tests.
EchoDiST is an unsupervised framework for estimating myocardial motion in echocardiography. It combines self‑distillation joint learning of anatomical segmentation and motion estimation with a diffusion‑conditioned network, requiring only limited anatomical annotations. The method achieves statistically significant improvements in anatomical alignment, strain assessment, and functional metrics across three datasets, outperforming seven other learning‑based approaches.
arXiv:2604. 06482v2 Announce Type: replace-cross Abstract: Time-resolved volumetric MR imaging that reconstructs a 3D MRI within sub-seconds to resolve deformable motion is essential for motion-adaptive radiotherapy.
MoSAIK (Motion Search with AI in K-space) is a new method that retrospectively estimates in-plane rigid-body motion directly from standard multi-coil TSE k-space data without requiring motion-free references, external navigators, or additional acquisitions. It uses a decoupled convolutional embedding and Transformer encoder to predict rotation and translation parameters, which are then incorporated into a motion-aware reconstruction. In both simulated and in-vivo tests, MoSAIK achieved low estimation errors and improved image quality, reducing visible artefacts while preserving anatomical detail.
arXiv:2607. 03299v1 Announce Type: cross Abstract: Real-time cardiac cine MRI enables visualization of the beating heart during free breathing, but severe undersampling and motion make reconstruction highly challenging.
MIGA is a scan‑specific framework for accelerated 3D multi‑echo MRI that uses shared anisotropic Gaussian geometry, a coordinate‑conditioned multi‑output amplitude network, and explicit echo‑specific phase variables. The method jointly optimizes all components from undersampled multi‑coil k‑space data without requiring fully sampled training data. Experiments demonstrate that MIGA outperforms existing methods across various imaging tasks and acceleration factors, especially under stronger undersampling, and offers a favorable quality‑cost balance among full‑volume multi‑echo reconstruction techniques.
The paper presents an anatomy‑aligned surface learning framework for reconstructing patient‑specific 4D myocardial surfaces from sparsely sampled short‑axis cine MRI. By parameterizing epicardial and endocardial surfaces on a shared circumferential‑longitudinal UV domain, the method transforms irregular 3D reconstruction into structured coordinate‑field completion, enabling explicit correspondence across subjects and cardiac phases. Experiments on three public datasets show the approach outperforms mesh‑based and implicit methods, achieving Chamfer distances around 2.6–2.9 mm and preserving ventricular function with small errors in volume and ejection fraction.
The paper presents a primitive‑based framework for reconstructing dynamic contrast‑enhanced MRI at high undersampling rates. It separates anatomy, contrast dynamics, and motion into distinct temporal basis functions, allowing a geometric interpretation of the data. The method matches conventional reconstruction quality and accurately extracts aorta and kidney enhancement curves, with a modular design that can accommodate additional dynamic factors and higher acceleration.
Patient-specific 4D myocardial reconstruction from cine MRI supports quantitative functional assessment, regional motion analysis, and simulation-based modeling. However, routinely acquired short-axis...
arXiv:2610.05603v2 Announce Type: replace Abstract: Echocardiography is the most widely used cardiac imaging modality, yet interpretation demands integrating visual evidence across global anatomy, lo...
arXiv:2601. 13236v3 Announce Type: replace-cross Abstract: Parallel imaging techniques reduce magnetic resonance imaging (MRI) scan time but image quality degrades as the acceleration factor increases.