BEAM3R is a dose estimation framework that operates in beam’s-eye-view (BEV) for both photon and proton beamlet calculations. It uses a Mamba‑3 state‑space depth‑sequence core combined with physics‑based transport conditioning, sharing a 2D CNN encoder‑decoder architecture to process per‑plane BEV slices. The system achieves high accuracy on the DoseRAD2026 challenge, with local gamma pass rates above 96% for CT‑based models and runtimes under 25 s for photon and 18 s for proton predictions.
arXiv:2609.01018v1 Announce Type: cross Abstract: Architecture category. Hybrid method: a physics-based analytical pencil-beam (PB) dose engine followed by a 3-D convolutional residual-correction net...
arXiv:2603.23295v2 Announce Type: replace Abstract: Radiotherapy workflows for oncological patients increasingly rely on multi-modal medical imaging, commonly involving both Magnetic Resonance Imagin...
arXiv:2602. 05387v2 Announce Type: replace-cross Abstract: MRI provides superior soft tissue contrast without ionizing radiation; however, the absence of electron density information limits its direct use for dose calculation.
arXiv:2605.20470v2 Announce Type: replace-cross Abstract: Cone-beam CT (CBCT) is routinely acquired during radiotherapy for patient setup, but its quantitative reliability is degraded by scatter, noi...
The paper introduces a one‑pass conditional 3D rectified flow (3D Flow) framework for denoising whole‑body PET images, employing an optimized non‑uniform sampling strategy and a linear‑interpolant velocity‑matching objective. It reconstructs a full 3D volume in about 30 seconds, dramatically faster than multi‑hour 3D diffusion models, while maintaining high global image quality and lesion conspicuity even at ultra‑low doses (down to 1/100 of standard). Zero‑shot transfer tests on independent clinical data demonstrate robust performance across datasets and unseen dose levels.
arXiv:2607. 11941v1 Announce Type: cross Abstract: Computed tomography (CT) is a critical imaging modality for clinical diagnosis, but reducing radiation dose inevitably introduces severe noise and structured artifacts that degrade image quality.
arXiv:2509. 21913v2 Announce Type: replace-cross Abstract: Background: Cone-beam computed tomography CBCT is a commonly used modality for image guided radiotherapy.
arXiv:2606. 29592v1 Announce Type: new Abstract: A central premise of autonomous scientific imaging is that smarter navigation, whether Bayesian, RL-based, or otherwise adaptive, is the principal lever for sample-efficient acquisition.
The paper introduces Conditional Diffusion Posterior Alignment (CDPA), a method that scales diffusion-based sparse‑view CT reconstruction to large 3D volumes by conditioning a 2D U‑Net diffusion model on an initial 3D reconstruction and enforcing data‑consistency alignment. CDPA addresses high memory demands, limited 3D training data, and slice‑wise inconsistencies, achieving state‑of‑the‑art performance on synthetic and real Cone Beam CT data. The authors also demonstrate that the same approach improves fast denoising U‑Nets, delivering near‑diffusion quality at a fraction of the computational cost.
The paper introduces Dose-Aware Cold Diffusion (DACD), a physics-consistent framework that treats radiation dose as a continuous latent variable in a cold diffusion process for low-dose CT reconstruction. DACD combines dose-aware perception, multi-scale structural priors, and dose-calibrated step allocation to guide denoising, and adds an iterative forward-backprojection correction to enforce projection-domain consistency. Experiments on Mayo-2020, Mayo-2016, and LoDoPaB-CT show DACD outperforms existing diffusion-based and physics-guided methods, especially at ultra-low doses, and generalizes robustly across continuous, unseen dose levels.
arXiv:2608. 08713v1 Announce Type: cross Abstract: Vision-language models offer a promising path toward automating radiology report generation, but applying them to full 3D CT volumes poses substantial computational challenges.
arXiv:2608. 08919v1 Announce Type: cross Abstract: During standard radiotherapy planning, repeated CT acquisitions are often required for patient registration, verification, and adaptive planning, resulting in increased cumulative X-ray dose.