Methodology for simulating x-ray sources of computed tomography systems using GATE 10 without manufacturer data [0.03%]
基于GATE 10的CT系统X射线源模拟方法学研究无需制造商数据
Anh Thu Lê,Gaëtan Raymond,Rékia Sidibé et al.
Anh Thu Lê et al.
This study aims to implement and evaluate a source modeling method for Monte Carlo (MC) simulation of computed tomography (CT) systems in the absence of manufacturer data. This work enables simulation of realistic CT x-ray sources by integr...
A deep learning-based framework for patient-specific radiation dose prediction in beta-emitting radionuclide therapies [0.03%]
基于深度学习的特定患者放射性核素治疗辐射剂量预测框架
Sangseok Ha,Hyera Kang,Dong-San Kang et al.
Sangseok Ha et al.
Objective: Conventional image-based models for radionuclide therapy dosimetry are typically radionuclide-specific and rely on nuclear medicine (NM) images for training. We developed a deep learning (DL) model that predict...
NNTV-GS：A fast reconstruction method combining nearest neighbor total variation and Gaussian splatting in dental offset detector CBCT [0.03%]
结合最近邻总变化和高斯释光的快速重建方法在口腔偏移检测CBCT中的应用(NNTV-GS)
Yuyang Wang,Yuqi Liang,Xiaomo Liu et al.
Yuyang Wang et al.
Objective: This study aims to address the slow reconstruction speed of iterative reconstruction algorithms in dental cone-beam computed tomography (CBCT) imaging while enhancing reconstruction accuracy. Specifically, the ...
Automated daily adaptation for breast cancer radiotherapy: benefits of deep learning-driven dose prediction workflow for CBCT-based adaptation [0.03%]
基于CBCT适应的深度学习驱动剂量预测工作流程的每日乳腺癌放射治疗自动化适应的好处
Nina Pesonen,Tuomas Viren,Mikko Mankinen et al.
Nina Pesonen et al.
Objective
Daily anatomical variations can jeopardize the quality of modern radiotherapy (RT). Adaptive radiotherapy (ART) aims to address this by adjusting treatment plans according to the patient's daily anatomy. However, as implementa...
SSI-Net: A hybrid physics-constrained deep learning framework for quantitative ultrasound speed-of-sound reconstruction [0.03%]
一种基于物理的深度学习超声波重建速度框架
Zheng Sun,Qian Jiang,Zhangshuo Gao et al.
Zheng Sun et al.
Objective: Quantitative ultrasound tomography faces challenges in reconstructing speed‑of‑sound (SoS) distributions due to the ill‑posed nature of the inverse problem and the computational complexity of full‑waveform ...
Variance reduction with synaptic density imaging in Parkinson's disease using direct-4D PET image reconstruction [0.03%]
基于直接4D PET图像重建的帕金森病突触密度成像方差降低研究
Paul Gravel,Jean-Dominique Gallezot,Kathryn Fontaine et al.
Paul Gravel et al.
Direct reconstruction (DR) of parametric images from dynamic PET data has been shown to provide substantial noise reduction compared to the conventional indirect reconstruction (IR) approach where frames are first reconstructed and then vox...
Estimating time-dependent cell survival in particle beam thermoradiotherapy with the dynamic temperature-dependent stochastic microdosimetric kinetic model [0.03%]
基于动态温度依赖的随机微剂量学动力学模型估计粒子束热放疗中时间相关的细胞生存率
Yuki Kase,Shotaro Nakahara,Yoshitaka Matsumoto
Yuki Kase
Optimizing particle beam thermoradiotherapy is hindered by the lack of methods to quantify the biological effects of temporal temperature changes. This study proposes the "dynamic Temperature-dependent Stochastic Microdosimetric Kinetic (TS...
Functional-based multi-omics early prediction of radiation pneumonitis in NSCLC using AI-generated perfusion and ventilation from planning CT [0.03%]
基于功能的多组学早期内照射性肺炎预测非小细胞肺癌放疗后肺损伤的深度学习方法研究
Mayang Zhao,Tao Peng,Zhi Chen et al.
Mayang Zhao et al.
ObjectiveThis study aims to develop a functional-based multi-omics model for early prediction of radiation pneumonitis (RP) by extracting radiomic and dosiomic features from functionally defined lung regions, using generated perfusion (Q) a...
Comparing energy-integrating detector and photon-counting detector-based breast cone beam CTs for microcalcification detection via Monte Carlo simulation [0.03%]
基于蒙特卡罗模拟的能量积分检测器和光子计数检测器乳腺锥形束CT的微钙化检测比较研究
Ahad Ezzati,Xiaoyu Hu,Miao Qi et al.
Ahad Ezzati et al.
Microcalcification ($/mu$Calc) detection plays an important role in breast cancer screening. Electronic noise in energy-integrating detectors (EID) is the major challenge for this task in current breast cone beam CT (bCBCT) due to the tight...
Evaluation of proton range differences in photon-counting and dual-energy computed tomography across imaging doses and anthropomorphic phantom sizes [0.03%]
基于光子计数和双能量CT成像剂量及人体尺寸的质子射程差异评估研究
Didier Lustermans,Gabriel Paiva Fonseca,Gloria Vilches-Freixas et al.
Didier Lustermans et al.
In proton therapy, dual-energy computed tomography (DECT) has shown to improve proton range estimation and treatment planning, but it is not yet widely implemented clinically as technology differences may restrict application (e.g. field-of...