Landmark-guided deformable image registration for accurate cumulative dose evaluation in lung reirradiation [0.03%]
基于地标的肺再照射累积剂量评估的精确配准方法研究
Marija Popovic,Marco di Francesco,Neil Kopek et al.
Marija Popovic et al.
Background and purpose: Dose summation in thoracic reirradiation is challenging due to anatomical changes and limitations of rigid image registration. Deformable image registration offers improved accuracy but requires ca...
Standardized reporting as a foundation for trustworthy and reproducible artificial intelligence in radiotherapy [0.03%]
基于可信赖且可重复的人工智能的放射治疗标准化报告制度基础研究
Kareem A Wahid,William H Nailon,Timothy D Solberg
Kareem A Wahid
Direct integration of deep learning-based GTV auto-segmentation into a clinical radiotherapy planning system [0.03%]
基于深度学习的GTV自动勾画直接整合进临床放射治疗计划系统中
Bao Ngoc Huynh,Cecilia Marie Futsaether,Oliver Tomic et al.
Bao Ngoc Huynh et al.
Manual Gross Tumor Volume (GTV) delineation for radiotherapy is time‑consuming and prone to inter‑observer variability. Deep Learning (DL)-based auto‑segmentation offers faster and more consistent solutions, but translation into clinical...
Impact of reduced robustness settings on the necessity for proton therapy treatment plan adaptation in head-and-neck cancer patients [0.03%]
降低鲁棒性设置对头颈部癌症患者质子治疗计划修订的影响研究
Brian Zapien-Campos,Dirk Wagenaar,Tim Franssen et al.
Brian Zapien-Campos et al.
Background and purpose: Robust optimization mitigates the effects of range and setup uncertainties in intensity-modulated proton therapy (IMPT) through robustness settings. However, it increases the dose to organs-at-risk...
Large language models for scalable standardization in radiation oncology [0.03%]
用于放射肿瘤学可扩展标准化的大规模语言模型
Warren Floyd,Kareem A Wahid,Brian Anderson et al.
Warren Floyd et al.
Automatic segmentation of the urethra and prostate zones with deep learning on T2-weighted magnetic resonance imaging [0.03%]
基于T2加权磁共振成像的深度学习驱动的尿道及前列腺分区自动分割技术
William Holmlund,Attila Simkó,Karin Söderkvist et al.
William Holmlund et al.
Background and purpose: Accurate segmentation of the urethra is crucial for safe focal dose escalated radiotherapy, while prostate zone identification is important for prostate cancer diagnosis. Manual delineations on mag...
Geometric accuracy of surface high-dose rate brachytherapy applicator and catheters identified using Dixon volumetric interpolated breath-hold examination magnetic resonance images [0.03%]
利用Dixon体积插值屏气磁共振图像识别表面高剂量率组织间近距离治疗模板及施源器的几何精度
Evangelia Kaza,Ivan Buzurovic
Evangelia Kaza
Background and purpose: Volumetric Interpolated Breath-hold Examination (VIBE) magnetic resonance imaging (MRI) can depict flap applicators of High-Dose-Rate (HDR) surface brachytherapy. Evaluating criteria for catheter d...
Geometry-based framework for beam angle selection in proton therapy for lung cancer [0.03%]
基于几何的质子治疗肺癌束流角度选择框架
Kyriakos Fotiou,Per-Ivar Lønne,Eirik Malinen
Kyriakos Fotiou
Background and purpose: Proton therapy is a promising modality for treating locally advanced non-small cell lung cancer (LA-NSCLC). However, respiratory-induced intra-fractional motion can compromise tumour coverage. This...
Automated deep learning segmentation and planning for left-sided breast radiotherapy with minimised adaptations based on dose, TCP and NTCP criteria [0.03%]
基于剂量、TCP和NTCP标准的最小适应下的左乳放疗自动化深度学习分割与计划
Niels van Acht,Andreea Ciobotaru,Maurice van der Sangen et al.
Niels van Acht et al.
Background and purpose: Deep learning segmentation (DLS) and planning (DLP) models in radiotherapy treatment planning increase consistency and reduce planning time. However, many DL segmentations and plans are manually ad...
Dosimetric intercomparison for stereotactic radiotherapy of multiple brain metastases [0.03%]
立体定向放射治疗多发脑转移瘤的剂量学比较研究
Sara Abdollahi,Rachid Boucenna,Cécile Chatelain et al.
Sara Abdollahi et al.
Background and purpose: Stereotactic radiotherapy (SRT) delivers high doses with submillimeter precision to small targets, requiring accuracy in both dose calculation and delivery. This study aimed to perform a dosimetric...