Inhomogeneity detection within a head-sized phantom using tracking of charged nuclear fragments in ion beam therapy [0.03%]
利用离子束治疗中带电核碎片的追踪在头部大小的模型中检测不均匀性
Renato Félix-Bautista,Laura Ghesquière-Diérickx,Pamela Ochoa-Parra et al.
Renato Félix-Bautista et al.
Objective.The highly conformal carbon-ion radiotherapy is associated with an increased sensitivity of the dose distributions to internal changes in the patient during the treatment course. Hence, monitoring methodologies capable of detectin...
Explainable AI for automated respiratory misalignment detection in PET/CT imaging [0.03%]
解释性人工智能在PET/CT成像自动呼吸定位误差检测中的应用
Yazdan Salimi,Zahra Mansouri,Mehdi Amini et al.
Yazdan Salimi et al.
Purpose.Positron emission tomography (PET) image quality can be affected by artifacts emanating from PET, computed tomography (CT), or artifacts due to misalignment between PET and CT images. Automated detection of misalignment artifacts ca...
Imaging error reduction in radial cine-MRI with deep learning-based intra-frame motion compensation [0.03%]
基于深度学习的帧内运动校正的心脏径向电影MRI成像误差降低方法
Zhuojie Sui,Prasannakumar Palaniappan,Chiara Paganelli et al.
Zhuojie Sui et al.
Objective.Radial cine-MRI allows for sliding window reconstruction at nearly arbitrary frame rate, promising high-speed imaging for intra-fractional motion monitoring in magnetic resonance guided radiotherapy. However, motion within the rec...
Robust optimization incorporating weekly predicted anatomical CTs in IMPT of nasopharyngeal cancer [0.03%]
基于每周预测解剖CT的强度调制质子治疗的头颈部肿瘤鲁棒优化计划研究
Mark Ka Heng Chan,Ying Zhang
Mark Ka Heng Chan
Objective.This study proposes a robust optimization (RO) strategy utilizing virtual CTs (vCTs) predicted by an anatomical model in intensity-modulated proton therapy (IMPT) for nasopharyngeal cancer (NPC).Methods and Materials.For ten NPC p...
Proton ARC based LATTICE radiation therapy: feasibility study, energy layer optimization and LET optimization [0.03%]
基于质子ARC的LATTICE放射治疗：可行性研究，能量层优化和LET优化
Ya-Nan Zhu,Weijie Zhang,Jufri Setianegara et al.
Ya-Nan Zhu et al.
Objective.LATTICE, a spatially fractionated radiation therapy (SFRT) modality, is a 3D generalization of GRID and delivers highly modulated peak-valley spatial dose distribution to tumor targets, characterized by peak-to-valley dose ratio (...
Assessing suitability and stability of materials for a head and neck anthropomorphic multimodality (MRI/CT) phantoms for radiotherapy [0.03%]
头颈部多模态(MRI/CT)放射治疗类人组织体模的材料选择及稳定性评价
Meshal Alzahrani,David A Broadbent,Irvin Teh et al.
Meshal Alzahrani et al.
Objective:This study aims to identify and evaluate suitable and stable materials for developing a head and neck anthropomorphic multimodality phantom for radiotherapy purposes. These materials must mimic human head and neck tissues in both ...
Xin Zhang,Jixiong Xie,Ting Su et al.
Xin Zhang et al.
Objective.The aim of this study was to investigate the impact of the bowtie filter on the image quality of the photon-counting detector (PCD) based CT imaging.Approach.Numerical simulations were conducted to investigate the impact of bowtie...
Study of modulation in complex refractive indices induced by ultrafast relativistic electrons using infrared and THz probe pulses [0.03%]
利用红外和太赫兹探针脉冲研究超快相对论电子诱导的复折射率调制现象的研究
Diana Jeong,Hyeon Sang Bark,Yushin Kim et al.
Diana Jeong et al.
Objective.Achieving ultra-precise temporal resolution in ionizing radiation detection is essential, particularly in positron emission tomography, where precise timing enhances signal-to-noise ratios and may enable reconstruction-less imagin...
Sparse-Laplace hybrid graph manifold method for fluorescence molecular tomography [0.03%]
用于荧光分子成像的稀疏拉普拉斯混合图流形法
Beilei Wang,Shuangchen Li,Heng Zhang et al.
Beilei Wang et al.
Objective.Fluorescence molecular tomography (FMT) holds promise for early tumor detection by mapping fluorescent agents in three dimensions non-invasively with low cost. However, since ill-posedness and ill-condition due to strong scatterin...
Deep learning-based automatic contour quality assurance for auto-segmented abdominal MR-Linac contours [0.03%]
基于深度学习的自动轮廓质量保证用于腹部MR-直线加速器自动分割轮廓
Mohammad Zarenia,Ying Zhang,Christina Sarosiek et al.
Mohammad Zarenia et al.
Objective.Deep-learning auto-segmentation (DLAS) aims to streamline contouring in clinical settings. Nevertheless, achieving clinical acceptance of DLAS remains a hurdle in abdominal MRI, hindering the implementation of efficient clinical w...