Multimodal feature-guided diffusion model for low-count PET image denoising [0.03%]
基于多模态特征引导扩散模型的低计数PET图像去噪方法
Gengjia Lin,Yuxi Jin,Zhenxing Huang et al.
Gengjia Lin et al.
Background: To minimize radiation exposure while obtaining high-quality Positron Emission Tomography (PET) images, various methods have been developed to derive standard-count PET (SPET) images from low-count PET (LPET) i...
Total brain dose estimation in single-isocenter-multiple-targets (SIMT) radiosurgery via a novel deep neural network with spherical convolutions [0.03%]
单中心多靶点放射神经外科中的一种新型球面卷积深度神经网络的总脑剂量估计方法
Zhenyu Yang,Mercedeh Khazaieli,Eugene Vaios et al.
Zhenyu Yang et al.
Background and purpose: Accurate prediction of normal brain dosimetric parameters is crucial for the quality control of single-isocenter multi-target (SIMT) stereotactic radiosurgery (SRS) treatment planning. Reliable dos...
Impact of nuclear fragmentation and irradiation scenarios on the dose-averaged LET, the RBE, and their relationship for H, He, C, O, and Ne ions [0.03%]
核碎裂和辐照方案对H、He、C、O和Ne离子的平均LET、RBE及其关系的影响
Alessio Parisi,Keith M Furutani,Chris J Beltran
Alessio Parisi
Background: Projectile and target fragmentation are nuclear phenomena that can influence the computation of the linear energy transfer (LET) and the relative biological effectiveness (RBE) in external radiotherapy with ac...
Analytical model for pulse pileup spectra and count statistics in photon counting detectors with seminonparalyzable behavior [0.03%]
具有半非截获行为的光子计数探测器的脉冲堆积光谱和计数统计分析模型
Yirong Yang,Norbert J Pelc,Adam S Wang
Yirong Yang
Background: Photon counting detectors (PCDs) with energy discriminating capabilities enable quantitative imaging of materials. However, the accuracy of estimates may be substantially degraded due to pulse pileup effects (...
Quantifying the dosimetric accuracy of expiration-gated stereotactic lung radiotherapy [0.03%]
定量分析呼吸门控立体定向肺部放疗的剂量精度
Daan Hoffmans,Isabel Remmerts de Vries,Max Dahele et al.
Daan Hoffmans et al.
Background: In stereotactic body radiotherapy, a form of motion management is often applied to mobile lung tumors. Gated radiotherapy is such form of motion management in which the radiation beam is switched on or off dep...
Experimental validation of a comprehensive fluoroscopy peak skin dose model using four different computational phantoms [0.03%]
四种不同计算体模对全面透视峰值皮肤剂量模型的实验验证
Daniel Vergara,Rasha S Makkia,Zhimin Li et al.
Daniel Vergara et al.
Background: Accurately determining the Peak Skin Dose (PSD) delivered to the patient during Fluoroscopically Guided Interventional Procedures (FGIP) is crucial for assessing potential radiation-induced skin injuries and d...
An MR-only deep learning inference model-based dose estimation algorithm for MR-guided adaptive radiation therapy [0.03%]
基于MR引导自适应放射治疗的MR-only深度学习推断模型剂量估计算法
Zhiqiang Liu,Kuo Men,Weigang Hu et al.
Zhiqiang Liu et al.
Background: Magnetic resonance-guided adaptive radiation therapy (MRgART) systems combine Magnetic resonance imaging (MRI) technology with linear accelerators (LINAC) to enhance the precision and efficacy of cancer treatm...
A robotic treatment delivery system to facilitate dynamic conformal synchrotron radiotherapy [0.03%]
用于动态共面同步放射治疗的机器人输送系统
Micah J Barnes,Nader Afshar,Taran Batty et al.
Micah J Barnes et al.
Background: In clinical radiotherapy, the patient remains static during treatment and only the source is dynamically manipulated. In synchrotron radiotherapy, the beam is fixed, and is horizontally wide and vertically sma...
Quantitative susceptibility mapping via deep neural networks with iterative reverse concatenations and recurrent modules [0.03%]
基于迭代反向拼接和循环模块的深度神经网络的定量磁化率映射技术
Min Li,Chen Chen,Zhuang Xiong et al.
Min Li et al.
Background: Quantitative susceptibility mapping (QSM) is a post-processing magnetic resonance imaging (MRI) technique that extracts the distribution of tissue susceptibilities and holds significant promise in the study of...
S2Net: Self-adaptive weighted fusion and self-adaptive aligned network for multi-modal MRI segmentation [0.03%]
S2Net：用于多模态MRI分割的自适应加权融合与自适应对齐网络
Chengzhi Gui,Xingwei An,Shuang Liu et al.
Chengzhi Gui et al.
Background: Accurate segmentation of lesions is beneficial for quantitative analysis and precision medicine in multimodal magnetic resonance imaging (MRI). ...