نتایج جستجو برای: deformable image registration dir
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Introduction Deformable image registration (DIR) is used to modify structures according to anatomical changes for observing the dosimetric effect. In this study, megavoltage computed tomography (MVCT) images were used to generate cumulative doses for nasopharyngeal cancer (NPC) patients by various DIR methods. The performance of the multiple DIR methods was analysed, and the impact of dose accu...
Quantum noise is common in CT images and is a persistent problem in accurate ventilation imaging using 4D-CT and deformable image registration (DIR). This study focuses on the effects of noise in 4D-CT on DIR and thereby derived ventilation data. A total of six sets of 4D-CT data with landmarks delineated in different phases, called point-validated pixel-based breathing thorax models (POPI), we...
PURPOSE We evaluated the performance of organ contour propagation from a planning computed tomography to cone-beam computed tomography with deformable image registration by comparing contours to manual contouring. MATERIALS AND METHODS Sixteen patients were retrospectively identified based on showing considerable physical change throughout the course of treatment. Multiple organs in the 3 reg...
BACKGROUND Re-contouring of structures on consecutive planning computed tomography (CT) images for patients that exhibit anatomical changes is elaborate and may negatively impact the turn-around time if this is required for many patients. This study was therefore initiated to validate the accuracy and usefulness of automatic contour propagation for head and neck cancer patients using SmartAdapt...
Abstract We assessed the accuracy of deformable image registration (DIR) between CT and MR images using an open-source software (Elastix, from Utrecht Medical Center) a commercial (Velocity AI Ver. 3.2.0 Varian Systems, Palo Alto, CA, USA) software. Five male patients’ pelvic regions were studied publicly available CT, T1-weighted (T1w) MR, T2-weighted (T2w) images. In cost function Elastix, we...
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