ArticleZeitschrift fur medizinische Physik2013
A quantitative comparison of the performance of three deformable registration algorithms in radiotherapy.
Article in Zeitschrift fur medizinische Physik, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 28 citations in OpenAlex.
- Evaluation of MRI anatomy in machine learning predictive models to assess hydrogel spacer benefit for prostate cancer patients.Technical innovations & patient support in radiation oncology · 2025Article
- Quality assurance assessment of intra-acquisition diffusion-weighted and T2-weighted magnetic resonance imaging registration and contour propagation for head and neck cancer radiotherapy.Medical physics · 2023Article
- Utility of deformable image registration for adaptive prostate cancer treatment. Analysis and comparison of two commercially available algorithms.Zeitschrift fur medizinische Physik · 2022Article
- Dosimetric study of Hounsfield number correction effect in areas influenced by contrast product in lungs case.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2021Article
- MRI based volumetric measurements of vestibular schwannomas in patients with neurofibromatosis type 2: comparison of three different software tools.Scientific reports · 2020Article
- Article
- A multiparametric method to assess the MIM deformable image registration algorithm.Journal of applied clinical medical physics · 2019Article
- Deformable registration of 3D ultrasound volumes using automatic landmark generation.PloS one · 2019Article
- A design of a DICOM-RT-based tool box for nonrigid 4D dose calculation.Journal of applied clinical medical physics · 2016Article
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Authors and funding
12 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
We present an evaluation of various non-rigid registration algorithms for the purpose of compensating interfractional motion of the target volume and organs at risk areas when acquiring CBCT image data prior to irradiation. Three different deformable registration (DR) methods were used: the Demons algorithm implemented in the iPlan Software (BrainLAB AG, Feldkirchen, Germany) and two custom-developed piecewise methods using either a Normalized Correlation or a Mutual Information metric (featureletNC and featureletMI). These methods were tested on data acquired using a novel purpose-built phantom for deformable registration and clinical CT/CBCT data of prostate and lung cancer patients. The Dice similarity coefficient (DSC) between manually drawn contours and the contours generated by a derived deformation field of the structures in question was compared to the result obtained with rigid registration (RR). For the phantom, the piecewise methods were slightly superior, the featureletNC for the intramodality and the featureletMI for the intermodality registrations. For the prostate cases in less than 50% of the images studied the DSC was improved over RR. Deformable registration methods improved the outcome over a rigid registration for lung cases and in the phantom study, but not in a significant way for the prostate study. A significantly superior deformation method could not be identified.
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