ArticlePhysics and imaging in radiation oncology2021
Comparison of atlas-based auto-segmentation accuracy for radiotherapy in prostate cancer.
Article in Physics and imaging in radiation oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Geometric evaluation of a deep learning method for segmentation of urinary OARs on magnetic resonance imaging for prostate cancer radiotherapy.Clinical and translational radiation oncology · 2026Article
- Clinical evaluation of atlas-based auto-segmentation for contouring pelvic CTVs in the treatment of anal cancer with FDG-PET-positive lymph node involvement.Frontiers in oncology · 2025Article
- Impact of Artificial Intelligence-Based Autosegmentation of Organs at Risk in Low- and Middle-Income Countries.Advances in radiation oncology · 2024Article
- Artificial Intelligence-Based Autosegmentation: Advantages in Delineation, Absorbed Dose-Distribution, and Logistics.Advances in radiation oncology · 2024Article
- Real-world validation of Artificial Intelligence-based Computed Tomography auto-contouring for prostate cancer radiotherapy planning.Physics and imaging in radiation oncology · 2023Article
- A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy.Radiation oncology (London, England) · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Atlas-based auto-segmentation (ABS) procedure used in radiotherapy can be classified into two groups, one using one atlas per patient (sSM) and the other using multiple atlases (sMM). This study evaluated auto-contouring accuracy and contouring time in patients with prostate cancer using the two procedures. The Dice similarity coefficient of sMM was significantly better than that of sSM (prostate [median, 0.81 (range, 0.66-0.91) vs. 0.64 (0.27-0.71),
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Registered trials
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