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Objective. The objective of the presented study was to evaluate the feasibility of a coded-mask (CM) gamma camera for real-time range verification in proton therapy, addressing the need for a precise and efficient method of treatment…

Objective. Prompt-gamma imaging encompasses several approaches for online monitoring of beam range or deposited dose distribution in proton therapy. We test one of the imaging techniques - a coded mask approach - both experimentally and via…

Medical imaging applications are highly specialized in terms of human anatomy, pathology, and imaging domains. Therefore, annotated training datasets for training deep learning applications in medical imaging not only need to be highly…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Arjun Krishna , Ge Wang , Klaus Mueller

With X-ray radiation protection and dose management constantly gaining interest in interventional radiology, novel procedures often undergo prospective dose studies using anthropomorphic phantoms to determine expected dose values. Due to…

With the success of 2D and 3D visual generative models, there is growing interest in generating 4D content. Existing methods primarily rely on text prompts to produce 4D content, but they often fall short of accurately defining complex or…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Hao Zhang , Di Chang , Fang Li , Mohammad Soleymani , Narendra Ahuja

Multi-planar tagged MRI is the gold standard for regional heart wall motion evaluation. However, accurate recovery of the 3D true heart wall motion from a set of 2D apparent motion cues is challenging, due to incomplete sampling of the true…

Image and Video Processing · Electrical Eng. & Systems 2024-12-10 Meng Ye , Bingyu Xin , Bangwei Guo , Leon Axel , Dimitris Metaxas

Purpose: Digital phantoms are one of the key components of virtual imaging trials (VITs) that aim to assess and optimize new medical imaging systems and algorithms. However, these phantoms vary in their voxel resolution, appearance, and…

Medical Physics · Physics 2024-02-02 Amar Kavuri , Mini Das

Purpose: Bone metastasis have a major impact on the quality of life of patients and they are diverse in terms of size and location, making their segmentation complex. Manual segmentation is time-consuming, and expert segmentations are…

Image and Video Processing · Electrical Eng. & Systems 2024-09-18 Emile Saillard , Aurélie Levillain , David Mitton , Jean-Baptiste Pialat , Cyrille Confavreux , Hélène Follet , Thomas Grenier

Monte Carlo (MC) simulation of linacs depends on the accurate geometrical description of the head. The geometry of the Varian TrueBeam (TB) linac is not available to researchers. Instead, the company distributes phase-space files (PSFs) of…

In medical image segmentation, particularly in UNet-like architectures, upsampling is primarily used to transform smaller feature maps into larger ones, enabling feature fusion between encoder and decoder features and supporting multi-scale…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Chengkun Sun , Jinqian Pan , Renjie Liang , Zhengkang Fan , Xin Miao , Jiang Bian , Jie Xu

Estimating the shape and motion state of the myocardium is essential in diagnosing cardiovascular diseases.However, cine magnetic resonance (CMR) imaging is dominated by 2D slices, whose large slice spacing challenges inter-slice shape…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Xiaohan Yuan , Cong Liu , Yangang Wang

Particle therapy is an established method to treat deep-seated tumours using accelerator-produced ion beams. For treatment planning, the precise knowledge of the relative stopping power (RSP) within the patient is vital. Conversion errors…

Monte Carlo (MC) simulation is considered as the most accurate method for radiation dose calculations. Accuracy of a source model for a linear accelerator is critical for the overall dose calculation accuracy. In this paper, we presented an…

Medical Physics · Physics 2015-03-06 Zhen Tian , Yongbao Li , Michael Folkerts , Feng Shi , Steve B. Jiang , Xun Jia

Diffusion models produce high-quality synthetic data but suffer from slow inference. We propose 3D Variable-Step Denoising Diffusion Probabilistic Model (VS-DDPM) a framework engineered to maintain generative quality while accelerating…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Nikoo Moradi , Gijs Luijten , Behrus Hinrichs-Puladi , Jens Kleesiek , Victor Alves , Jan Egger , André Ferreira

Particle physics simulations are the cornerstone of nuclear engineering applications. Among them radiotherapy (RT) is crucial for society, with 50% of cancer patients receiving radiation treatments. For the most precise targeting of tumors,…

Machine Learning · Computer Science 2021-09-10 Oscar Pastor-Serrano , Zoltán Perkó

Simulation-guided design represents a fundamental contribution towards the development of modern semiconductor devices aiming to reach high-performance particle detection, identification and tracking, and constitutes a strategic element of…

Instrumentation and Detectors · Physics 2025-05-12 Marco Mandurrino

4D scans of dynamic deformable human body parts help researchers have a better understanding of spatiotemporal features. However, reconstructing 4D scans based on multiple asynchronous cameras encounters two main challenges: 1) finding the…

Image and Video Processing · Electrical Eng. & Systems 2023-07-25 Farzam Tajdari , Toon Huysmans , Xinhe Yao , Jun Xu , Yu Song

Transrectal biopsies under 2D ultrasound (US) control are the current clinical standard for prostate cancer diagnosis. The isoechogenic nature of prostate carcinoma makes it necessary to sample the gland systematically, resulting in a low…

Computer Vision and Pattern Recognition · Computer Science 2011-07-11 Michael Baumann , Pierre Mozer , Vincent Daanen , Jocelyne Troccaz

The validation, verification, and uncertainty quantification of computationally expensive theoretical models of quantum many-body systems require the construction of fast and accurate emulators. In this work, we develop emulators for…

We propose a new class of structured methods for Monte Carlo (MC) sampling, called DPPMC, designed for high-dimensional nonisotropic distributions where samples are correlated to reduce the variance of the estimator via determinantal point…

Machine Learning · Computer Science 2019-05-31 Krzysztof Choromanski , Aldo Pacchiano , Jack Parker-Holder , Yunhao Tang
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