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相关论文: Geometric and Dosimetric Validation of Deformable …

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Purpose: Deformable image registration (DIR) is critical in adaptive radiation therapy (ART) to account for anatomical changes. Conventional intensity-based DIR methods often fail when image intensities differ. This study evaluates a hybrid…

医学物理 · 物理学 2024-11-27 Keyur D. Shah , James A. Shackleford , Nagarajan Kandasamy , Gregory C. Sharp

Background: Accurate deformable image registration (DIR) is required for contour propagation and dose accumulation in MR-guided adaptive radiotherapy (MRgART). This study trained and evaluated a deep learning DIR method for domain invariant…

Anatomical motion and deformation pose challenges to the understanding of the delivered dose distribution during radiotherapy treatments. Hence, deformable image registration (DIR) algorithms are increasingly used to map contours and dose…

医学物理 · 物理学 2021-09-22 Emily Cloutier , Luc Beaulieu , Louis Archambault

Objective: Clinical implementation of deformable image registration (DIR) requires voxel-based spatial accuracy metrics such as manually identified landmarks, which are challenging to implement for highly mobile gastrointestinal (GI)…

In adaptive radiotherapy, deformable image registration is often conducted between the planning CT and treatment CT (or cone beam CT) to generate a deformation vector field (DVF) for dose accumulation and contour propagation. The auto…

医学物理 · 物理学 2015-06-12 Xuejun Gu , Bin Dong , Jing Wang , John Yordy , Loren Mell , Xun Jia , Steve B. Jiang

Deformable image registration (DIR) is a crucial tool in radiotherapy for analyzing anatomical changes and motion patterns. Current DIR implementations rely on discrete volumetric motion representation, which often leads to compromised…

医学物理 · 物理学 2025-07-22 Xia Li , Runzhao Yang , Muheng Li , Xiangtai Li , Antony J. Lomax , Joachim M. Buhmann , Ye Zhang

Background and Purpose: Voxel-based analysis (VBA) helps to identify dose-sensitive regions by aligning individual dose distributions within a common coordinate system (CCS). Accurate deformable image registration (DIR) is essential for…

医学物理 · 物理学 2025-09-26 Xingyue Ruan , Xia Li , Muheng Li , Barbara Bachtiary , Antony Lomax , Zhiling Chen , Ye Zhang

Plastic scintillation detectors are increasingly used to measure dose distributions in the context of radiotherapy treatments. Their water-equivalence, real-time response and high spatial resolution distinguish them from traditional…

医学物理 · 物理学 2021-09-22 Emily Cloutier , Louis Archambault , Luc Beaulieu

Proton therapy offers superior organ-at-risk sparing but is highly sensitive to anatomical changes, making accurate deformable image registration (DIR) across longitudinal CT scans essential. Conventional DIR methods are often too slow for…

Computed tomography (CT) to cone-beam computed tomography (CBCT) deformable image registration (DIR) is a crucial step in adaptive radiation therapy. Current intensity-based registration algorithms, such as demons, may fail in the context…

医学物理 · 物理学 2017-08-23 Xin Zhen , Xuejun Gu , Hao Yan , Linghong Zhou , Xun Jia , Steve B. Jiang

The accuracy of deformable image registration (DIR) has a significant dosimetric impact in radiation treatment planning. We evaluated accuracy of various DIR algorithms using variations of the deformation point and volume. The reference…

Cone-beam CT (CBCT)-based online adaptive radiotherapy calls for accurate auto-segmentation to reduce the time cost for physicians to edit contours. However, deep learning (DL)-based direct segmentation of CBCT images is a challenging task,…

医学物理 · 物理学 2023-02-22 Xiao Liang , Howard Morgan , Ti Bai , Michael Dohopolski , Dan Nguyen , Steve Jiang

Purpose: Accurate 3D MRI-ultrasound (US) deformable registration is critical for real-time guidance in high-dose-rate (HDR) prostate brachytherapy. We present a weakly supervised spatial implicit neural representation (SINR) method to…

医学物理 · 物理学 2025-03-19 Jing Wang , Ruirui Liu , Yu Lei , Michael J. Baine , Tian Liu , Yang Lei

An MRI-only adaptive radiotherapy (ART) workflow is desirable for managing interfractional changes in anatomy, but producing synthetic CT (sCT) data through paired data-driven deep learning (DL) for abdominal dose calculations remains a…

Purpose. - Radiotherapy is an important treatment for prostate cancer.During treatment sessions, bladder and rectal repletion is difficult to quantify and cannot be measured with a single and initial CT scan acquisition. Some methods, such…

Online adaptive radiation therapy (ART) promises the ability to deliver an optimal treatment in response to daily patient anatomic variation. A major technical barrier for the clinical implementation of online ART is the requirement of…

Adaptive Radiotherapy (ART) is an emerging technique for treating cancer patients which facilitates higher delivery accuracy and has the potential to reduce toxicity. However, ART is also resource-intensive, requiring extra human and…

医学物理 · 物理学 2022-12-20 Rupesh Ghimire , Kevin L. Moore , Daniela Branco , Dominique L. Rash , Jyoti Mayadev , Xenia Ray

Purpose: Deformable Image Registration (DIR) can benefit from additional guidance using corresponding landmarks in the images. However, the benefits thereof are largely understudied, especially due to the lack of automatic landmark…

计算机视觉与模式识别 · 计算机科学 2023-02-28 Monika Grewal , Jan Wiersma , Henrike Westerveld , Peter A. N. Bosman , Tanja Alderliesten

Deformable image registration (DIR) is a crucial and challenging technique for aligning anatomical structures in medical images and is widely applied in diverse clinical applications. However, existing approaches often struggle to capture…

图像与视频处理 · 电气工程与系统科学 2025-08-26 Shayan Kebriti , Shahabedin Nabavi , Ali Gooya

Contouring of the target volume and Organs-At-Risk (OARs) is a crucial step in radiotherapy treatment planning. In an adaptive radiotherapy setting, updated contours need to be generated based on daily imaging. In this work, we leverage…

图像与视频处理 · 电气工程与系统科学 2020-02-19 Mohamed S. Elmahdy , Tanuj Ahuja , U. A. van der Heide , Marius Staring
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