ArticleJournal of applied clinical medical physics2016
Evaluation of the tool "Reg Refine" for user-guided deformable image registration.
Article in Journal of applied clinical medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
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- Effects of respiratory and cardiac motion on estimating radiation dose to the left ventricle during radiotherapy for lung cancer.Journal of applied clinical medical physics · 2023Article
- Individualized everolimus treatment for tuberous sclerosis-related angiomyolipoma promotes treatment adherence and response.Clinical kidney journal · 2022Article
- Quantitative assessment of intra- and inter-modality deformable image registration of the heart, left ventricle, and thoracic aorta on longitudinal 4D-CT and MR images.Journal of applied clinical medical physics · 2022Article
- Dosimetric variation in preoperative partial breast radiosurgery assessed by deformable image registrations.Journal of radiosurgery and SBRT · 2022Article
- Development of a physical geometric phantom for deformable image registration credentialing of radiotherapy centers for a clinical trial.Journal of applied clinical medical physics · 2021Article
- Atlas of sentinel lymph nodes in early breast cancer using single-photon emission computed tomography: implication for lymphatic contouring.Radiation oncology journal · 2021Article
- Synthetic CT Generation of the Pelvis in Patients With Cervical Cancer: A Single Input Approach Using Generative Adversarial Network.IEEE access : practical innovations, open solutions · 2021Article
- Deforming to Best Practice: Key considerations for deformable image registration in radiotherapy.Journal of medical radiation sciences · 2020Article
- Evaluation of Intensity- and Contour-Based Deformable Image Registration Accuracy in Pancreatic Cancer Patients.Cancers · 2019Article
- A multiparametric method to assess the MIM deformable image registration algorithm.Journal of applied clinical medical physics · 2019Article
- Towards a universal MRI atlas of the prostate and prostate zones : Comparison of MRI vendor and image acquisition parameters.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2019Article
- Usefulness of hybrid deformable image registration algorithms in prostate radiation therapy.Journal of applied clinical medical physics · 2019Article
- Validating Dose Uncertainty Estimates Produced by AUTODIRECT: An Automated Program to Evaluate Deformable Image Registration Accuracy.Technology in cancer research & treatment · 2017Article
- Characterizing Sensitive Cardiac Substructure Excursion Due to Respiration.Advances in radiation oncologyArticle
- Evaluation of Image Registration Accuracy for Tumor and Organs at Risk in the Thorax for Compliance With TG 132 Recommendations.Advances in radiation oncologyArticle
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
"Reg Refine" is a tool available in the MIM Maestro v6.4.5 platform (www.mim-software.com) that allows the user to actively participate in the deformable image registration process. The purpose of this work was to evaluate the efficacy of this tool and investigate strategies for how to apply it effectively. This was done by performing DIR on two publicly available ground-truth models, the Pixel-based Breathing Thorax Model (POPI) for lung, and the Deformable Image Registration Evaluation Project (DIREP) for head and neck. Image noise matched in both magnitude and texture to clinical CBCT scans was also added to each model to simulate the use case of CBCT-CT alignment. For lung, the results showed Reg Refine effective at improving registration accuracy when controlled by an expert user within the context of large lung deformation. CBCT noise was also shown to have no effect on DIR performance while using the MIM algorithm for this site. For head and neck, the results showed CBCT noise to have a large effect on the accuracy of registration, specifically for low-contrast structures such as the brain-stem and parotid glands. In these cases, the Reg Refine tool was able to improve the registration accuracy when controlled by an expert user. Several strategies for how to achieve these results have been outlined to assist other users and provide feedback for developers of similar tools.
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