ArticlePloS one2017
Comprehensive evaluation of ten deformable image registration algorithms for contour propagation between CT and cone-beam CT images in adaptive head & neck radiotherapy.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- A density assignment method for dose monitoring in head-and-neck radiotherapy.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2019Trial
- Comparison of deformable image registration algorithms for planning CT and CBCT in prostate cancer patients treated with external beam radiation therapy.Radiological physics and technology · 2026Article
- MUsculo-Skeleton-Aware (MUSA) deep learning for anatomically guided head-and-neck CT deformable registration.Medical image analysis · 2025Article
- Evaluation of the geometric and dosimetric accuracies of deformable image registration of targets and critical organs in prostate CBCT-guided adaptive radiotherapy.Journal of applied clinical medical physics · 2024Article
- A novel evaluation model of image registration for cone-beam computed tomography guided lung cancer radiotherapy.Thoracic cancer · 2024Article
- Review and recommendations on deformable image registration uncertainties for radiotherapy applications.Physics in medicine and biology · 2023Review
- Segmentation by test-time optimization for CBCT-based adaptive radiation therapy.Medical physics · 2023Article
- Relational reasoning network for anatomical landmarking.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- The geometric and dosimetric accuracy of kilovoltage cone beam computed tomography images for adaptive treatment: a systematic review.BJR open · 2023Article
- Comparison of an in-house hybrid DIR method to NiftyReg on CBCT and CT images for head and neck cancer.Journal of applied clinical medical physics · 2022Article
- Using neural networks to extend cropped medical images for deformable registration among images with differing scan extents.Medical physics · 2021Article
- Comparison of weekly and daily online adaptation for head and neck intensity-modulated proton therapy.Physics in medicine and biology · 2021Article
- Head-and-neck organs-at-risk auto-delineation using dual pyramid networks for CBCT-guided adaptive radiotherapy.Physics in medicine and biology · 2021Article
- Biomechanical modeling of radiation dose-induced volumetric changes of the parotid glands for deformable image registration.Physics in medicine and biology · 2020Article
- Pelvic multi-organ segmentation on cone-beam CT for prostate adaptive radiotherapy.Medical physics · 2020Article
- "Dose of the day" based on cone beam computed tomography and deformable image registration for lung cancer radiotherapy.Journal of applied clinical medical physics · 2020Article
- Deep Geodesic Learning for Segmentation and Anatomical Landmarking.IEEE transactions on medical imaging · 2019Article
- Early Changes in Serial CBCT-Measured Parotid Gland Biomarkers Predict Chronic Xerostomia After Head and Neck Radiation Therapy.International journal of radiation oncology, biology, physics · 2018Article
- Performance Evaluation of Deformable Image Registration Algorithms Using Computed Tomography of Multiple Lung Metastases.Technology in cancer research & treatmentArticle
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8 authors.
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Abstract
Deformable image registration (DIR) is a critical technic in adaptive radiotherapy (ART) for propagating contours between planning computerized tomography (CT) images and treatment CT/cone-beam CT (CBCT) images to account for organ deformation for treatment re-planning. To validate the ability and accuracy of DIR algorithms in organ at risk (OAR) contour mapping, ten intensity-based DIR strategies, which were classified into four categories-optical flow-based, demons-based, level-set-based and spline-based-were tested on planning CT and fractional CBCT images acquired from twenty-one head & neck (H&N) cancer patients who underwent 6~7-week intensity-modulated radiation therapy (IMRT). Three similarity metrics, i.e., the Dice similarity coefficient (DSC), the percentage error (PE) and the Hausdorff distance (HD), were employed to measure the agreement between the propagated contours and the physician-delineated ground truths of four OARs, including the vertebra (VTB), the vertebral foramen (VF), the parotid gland (PG) and the submandibular gland (SMG). It was found that the evaluated DIRs in this work did not necessarily outperform rigid registration. DIR performed better for bony structures than soft-tissue organs, and the DIR performance tended to vary for different ROIs with different degrees of deformation as the treatment proceeded. Generally, the optical flow-based DIR performed best, while the demons-based DIR usually ranked last except for a modified demons-based DISC used for CT-CBCT DIR. These experimental results suggest that the choice of a specific DIR algorithm depends on the image modality, anatomic site, magnitude of deformation and application. Therefore, careful examinations and modifications are required before accepting the auto-propagated contours, especially for automatic re-planning ART systems.
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