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Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment and surgical planning. Recent advances of convolutional networks have demonstrated higher accuracy than…

Computer Vision and Pattern Recognition · Computer Science 2019-09-25 Ling Zhang , Le Lu , Xiaosong Wang , Robert M. Zhu , Mohammadhadi Bagheri , Ronald M. Summers , Jianhua Yao

We propose a cascaded 3D diffusion model framework to synthesize high-fidelity 3D PET/CT volumes directly from demographic variables, addressing the growing need for realistic digital twins in oncologic imaging, virtual trials, and…

Image and Video Processing · Electrical Eng. & Systems 2025-05-29 Siyeop Yoon , Sifan Song , Pengfei Jin , Matthew Tivnan , Yujin Oh , Sekeun Kim , Dufan Wu , Xiang Li , Quanzheng Li

This work summarises the results of a comparison organized by EURADOS focused on the usage of the ICRP Reference Computational Phantoms. This activity aimed to provide training for the implementation of voxel phantoms in Monte Carlo…

Diffeomorphic deformable image registration ensures smooth invertible transformations across inspiratory and expiratory chest CT scans. Yet, in practice, deep learning-based diffeomorphic methods struggle to capture large deformations…

Image and Video Processing · Electrical Eng. & Systems 2024-11-13 Muhammad F. A. Chaudhary , Stephanie M. Aguilera , Arie Nakhmani , Joseph M. Reinhardt , Surya P. Bhatt , Sandeep Bodduluri

Purpose: This study aims to develop and evaluate a three channel denoising diffusion probabilistic model (DDPM) for synthesizing single breast dual view mammograms and to assess the impact of channel representations on image fidelity and…

This study proposes Scout-Dose-TCM for direct, prospective estimation of organ-level doses under tube current modulation (TCM) and compares its performance to two established methods. We analyzed contrast-enhanced chest-abdomen-pelvis CT…

Fiducial marker positions in projection image of cone-beam computed tomography (CBCT) scans have been studied to evaluate daily residual motion during breath-hold radiation therapy. Fiducial marker migration posed challenges in accurately…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Aimee Guo , Weihua Mao

Ultrasound computed tomography (USCT) is an emerging imaging modality for breast imaging that can produce quantitative images that depict the acoustic properties of tissues. Computer-simulation studies, also known as virtual imaging trials,…

Medical Physics · Physics 2022-06-24 Fu Li , Umberto Villa , Seonyeong Park , Mark A. Anastasio

Treatment planning system calculations in inhomogeneous regions may present significant inaccuracies due to loss of electronic equilibrium. In this study, three different dose calculation algorithms, pencil beam, collapsed cone, and…

Medical Physics · Physics 2015-03-12 Sung Jin Kim , Dong Ho Kim , Sung Kyu Kim

Background: Treatment verification with PET imaging in charged particle therapy is conventionally done by comparing measurements of spatial distributions with Monte Carlo (MC) predictions. However, decay curves can provide additional…

Research in manipulation of deformable objects is typically conducted on a limited range of scenarios, because handling each scenario on hardware takes significant effort. Realistic simulators with support for various types of deformations…

Robotics · Computer Science 2025-05-15 Priya Sundaresan , Rika Antonova , Jeannette Bohg

Diffusion Monte Carlo (DMC) based on fixed-node approximation has enjoyed significant developments in the past decades and become one of the go-to methods when accurate ground state energy of molecules and materials is needed. The remaining…

Chemical Physics · Physics 2023-08-07 Weiluo Ren , Weizhong Fu , Xiaojie Wu , Ji Chen

On the base of Diffusion Monte-Carlo method it is developed a new Complex Diffusion Monte-Carlo (CDMC) method allowing to simulate the quantum systems with complex wave function. There are no approximations on the calculation of modulus and…

Condensed Matter · Physics 2007-05-23 B. Abdullaev , M. Musakhanov , A. Nakamura

The Derivative Source Method (DSM) takes derivatives of a particle transport equation with respect to selected parameters and solves them via the standard Monte Carlo random walk simulation along with the original transport problem. The…

Computational Physics · Physics 2025-01-14 Ilham Variansyah , Ryan G. McClarren , Todd S. Palmer

Detailed pulmonary airway segmentation is a clinically important task for endobronchial intervention and treatment of peripheral located lung cancer lesions. Convolutional Neural Networks (CNNs) are promising tools for medical image…

Computer Vision and Pattern Recognition · Computer Science 2023-11-15 Minghui Zhang , Guang-Zhong Yang , Yun Gu

We address the problem of recovering a time-varying 4D distribution from a sparse sequence of 2D projections - analogous to novel-view synthesis from sparse cameras, but applied to the 4D transverse phase space density $\rho(x,p_x,y,p_y)$…

Accelerator Physics · Physics 2026-04-08 Alexander Scheinker , Alexander Plastun , Peter Ostroumov

Purpose: We propose a general framework for quantifying predictive uncertainties of dose-related quantities and leveraging this information in a dose mimicking problem in the context of automated radiation therapy treatment planning.…

Medical Physics · Physics 2021-09-08 Tianfang Zhang , Rasmus Bokrantz , Jimmy Olsson

Computer simulation plays a central role in modern day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of…

Purpose: The physical properties of yttrium-90 (90Y) allow for imaging with positron emission tomography/computed tomography (PET/CT). The increased sensitivity of long axial field-of-view (LAFOV) PET/CT scanners possibly allows to overcome…

Reducing scan times, radiation dose, and enhancing image quality for lower-performance scanners, are critical in low-dose PET imaging. Deep learning techniques have been investigated for PET image denoising. However, existing models have…