ArticleJournal of applied clinical medical physics2019
A multiparametric method to assess the MIM deformable image registration algorithm.
Article in Journal of applied clinical medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
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- Evaluation of loco-regional recurrences using deformable image registration after isotoxic high dose stereotactic body radiotherapy in localised pancreatic cancer.Clinical and translational radiation oncology · 2026Article
- Functional lung avoidance stereotactic body radiation therapy for central lung cancer patients.Quantitative imaging in medicine and surgery · 2025Article
- Investigating the necessity of adaptive radiotherapy in tomotherapy of head and neck cancer patients.Radiation oncology (London, England) · 2025Article
- Evaluation of model uncertainty in AI-based synthetic CT generation from CBCT for abdominal adaptive radiotherapy.Medical physics · 2025Article
- Real-time 3D synthetic MRI based on kV imaging for motion monitoring of abdominal radiotherapy in a conventional LINAC.Physics in medicine and biology · 2025Article
- Magnetic resonance guided adaptive post prostatectomy radiotherapy: Accumulated dose comparison of different workflows.Journal of applied clinical medical physics · 2024Article
- Are offline ART decisions for NSCLC impacted by the type of dose calculation algorithm?Technical innovations & patient support in radiation oncology · 2024Article
- Real-time 4D MRI using MR signature matching (MRSIGMA) on a 1.5T MR-Linac system.Physics in medicine and biology · 2023Article
- Article
- Development of an automated radiotherapy dose accumulation workflow for locally advanced high-risk prostate cancer - A technical report.Journal of medical radiation sciences · 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
- Evaluation of Intensity- and Contour-Based Deformable Image Registration Accuracy in Pancreatic Cancer Patients.Cancers · 2019Article
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12 authors.
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Abstract
A quantitative evaluation of the performances of the deformable image registration (DIR) algorithm implemented in MIM-Maestro was performed using multiple similarity indices. Two phantoms, capable of mimicking different anatomical bending and tumor shrinking were built and computed tomography (CT) studies were acquired after applying different deformations. Three different contrast levels between internal structures were artificially created modifying the original CT values of one dataset. DIR algorithm was applied between datasets with increasing deformations and different contrast levels and manually refined with the Reg Refine tool. DIR algorithm ability in reproducing positions, volumes, and shapes of deformed structures was evaluated using similarity indices such as: landmark distances, Dice coefficients, Hausdorff distances, and maximum diameter differences between segmented structures. Similarity indices values worsen with increasing bending and volume difference between reference and target image sets. Registrations between images with low contrast (40 HU) obtain scores lower than those between images with high contrast (970 HU). The use of Reg Refine tool leads generally to an improvement of similarity parameters values, but the advantage is generally less evident for images with low contrast or when structures with large volume differences are involved. The dependence of DIR algorithm on image deformation extent and different contrast levels is well characterized through the combined use of multiple similarity indices.
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