EP-1512: Adaptive planning on Tomotherapy with deformable registration
نویسندگان
چکیده
منابع مشابه
Accuracy of eight deformable image registration (DIR) methods for tomotherapy megavoltage computed tomography (MVCT) images
INTRODUCTION The application of deformable image registration (DIR) to megavoltage computed tomography (MVCT) images benefits adaptive radiotherapy. This study aims to quantify the accuracy of DIR for MVCT images when using different deformation methods assessed in a cubic phantom and nasopharyngeal carcinoma (NPC) patients. METHODS In the control studies, the DIR accuracy in air-tissue and t...
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Approximately 60% of cancer patients are treated with external beam radiotherapy at some point during disease management. Despite the extended time frame of fractionated therapy (4–6 weeks), radiation therapy planning is carried out based on information that is currently limited to a single 3D anatomical computed tomography scan at the onset of treatment. This concept may result in severe treat...
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Introduction: In brachytherapy, as in external radiotherapy, image-guidance plays an important role. For GYN treatments it is standard to acquire at least CT images and preferably MR images prior to each treatment and to calculate the dose of the day on each set of images. Then, the dose to the target and to the organs at risk (OAR) is calculated with worst case scenario from I...
متن کاملA contour-guided deformable image registration algorithm for adaptive radiotherapy.
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-propagated contours on the treatment CT may contain relatively large errors, especially in low-contrast regions. A clinician's inspection and editing of the propa...
متن کاملReliability-Driven, Spatially-Adaptive Regularization for Deformable Registration
We propose a reliability measure that identifies informative image cues useful for registration, and present a novel, data-driven approach to spatially adapt regularization to the local image content via use of the proposed measure. We illustrate the generality of this adaptive regularization approach within a powerful discrete optimization framework and present various ways to construct a spat...
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ژورنال
عنوان ژورنال: Radiotherapy and Oncology
سال: 2015
ISSN: 0167-8140
DOI: 10.1016/s0167-8140(15)41504-x