ArticleQuantitative imaging in medicine and surgery2021
Improving deformable image registration with point metric and masking technique for postoperative breast cancer radiotherapy.
Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Deformable image registration accuracy: impact of user-defined parameter selection on contour propagation for deep inspiration breath-hold and free breathing breast radiotherapy.BMC medical imaging · 2026Article
- Evaluation of tattoo reliability in breast cancer re-irradiation.Technical innovations & patient support in radiation oncology · 2025Article
- Optimising inter-patient image registration for image-based data mining in breast radiotherapy.Physics and imaging in radiation oncology · 2024Article
- Deep Learning for Medical Image-Based Cancer Diagnosis.Cancers · 2023Review
- Applying Multi-Metric Deformable Image Registration for Dose Accumulation in Combined Cervical Cancer Radiotherapy.Journal of personalized medicine · 2023Article
- The application of multiple metrics in deformable image registration for target volume delineation of breast tumor bed.Journal of applied clinical medical physics · 2022Article
- A Medical Image Registration Method Based on Progressive Images.Computational and mathematical methods in medicine · 2021Article
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Abstract
backgroundDeformable image registration (DIR) is increasingly used for target volume definition in radiotherapy. However, this method is challenging for postoperative breast cancer patients due to the large deformations and non-correspondence caused by tumor resection and clip insertion. In this study, an improved B-splines based DIR method was developed to address this issue for higher registration accuracy.
methodsThe conventional B-splines based DIR method was improved with the introduction of point metric and masking technique. The point metric minimizes the distance between 2 point sets with known correspondence for regularization of intensity-based B-splines registration. The masking technique reduces the influence of non-corresponding regions in breast computed tomography (CT) images. Two sets of CT images before and after breast surgery were used for image registration. One set was the diagnostic CT image acquired before surgery, and another set was the planning CT image acquired after surgery for breast cancer radiotherapy. A total of 26 sets of CT images from 13 patients were collected retrospectively for the test. The improved DIR method's registration accuracy was evaluated by target registration error (TRE), the Jacobian determinant, and visual assessment.
resultsFor soft tissue, the difference in the median TRE between the improved DIR method and the conventional DIR method was statistically significant (2.27
conclusionsThe improved DIR method's registration accuracy was higher than the conventional DIR method based on the preliminary results. With point metric and masking technique, the influence of large deformations and non-correspondence on registration between pre- and post-operative CT images can be effectively reduced. Therefore, this method provides a feasible way for target volume definition in postoperative breast cancer radiotherapy treatment planning.
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