ArticleRadiation oncology (London, England)2021
Geometric and dosimetric impact of 3D generative adversarial network-based metal artifact reduction algorithm on VMAT and IMPT for the head and neck region.
Article in Radiation oncology (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- HyperSight CBCT dose calculation accuracy for adaptive head and neck radiotherapy: Results from a prospective clinical trial.Medical physics · 2026Trial
- Deep learning-based metal artifact reduction in CT for head and neck radiotherapy.Physics and imaging in radiation oncology · 2026Review
- Comparison of Various GAN-Based Bone Suppression Imaging for High-Accurate Markerless Motion Tracking of Lung Tumors in CyberKnife Treatment.Thoracic cancer · 2025Article
- Prediction of prognosis in glioblastoma with radiomics features extracted by synthetic MRI images using cycle-consistent GAN.Physical and engineering sciences in medicine · 2024Article
- Deep learning-based ultrasound transducer induced CT metal artifact reduction using generative adversarial networks for ultrasound-guided cardiac radioablation.Physical and engineering sciences in medicine · 2023Article
- Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology Enterprise.Journal of clinical medicine · 2023Article
- Geometric and dosimetric evaluation of deep learning based auto-segmentation for clinical target volume on breast cancer.Journal of applied clinical medical physics · 2023Article
- Combined clustered scan-based metal artifact reduction algorithm (CCS-MAR) for ultrasound-guided cardiac radioablation.Physical and engineering sciences in medicine · 2022Article
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5 authors.
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Abstract
backgroundWe investigated the geometric and dosimetric impact of three-dimensional (3D) generative adversarial network (GAN)-based metal artifact reduction (MAR) algorithms on volumetric-modulated arc therapy (VMAT) and intensity-modulated proton therapy (IMPT) for the head and neck region, based on artifact-free computed tomography (CT) volumes with dental fillings.
methodsThirteen metal-free CT volumes of the head and neck regions were obtained from The Cancer Imaging Archive. To simulate metal artifacts on CT volumes, we defined 3D regions of the teeth for pseudo-dental fillings from the metal-free CT volumes. HU values of 4000 HU were assigned to the selected teeth region of interest. Two different CT volumes, one with four (m4) and the other with eight (m8) pseudo-dental fillings, were generated for each case. These CT volumes were used as the Reference. CT volumes with metal artifacts were then generated from the Reference CT volumes (Artifacts). On the Artifacts CT volumes, metal artifacts were manually corrected for using the water density override method with a value of 1.0 g/cm
resultsThe time required to generate a single GAN-MAR CT volume was approximately 30 s. The median SSIMs were lower in the m8 group than those in the m4 group, and ANOVA showed a significant difference in the SSIM for the m8 group (p < 0.05). Although the median differences in D
conclusionsThe GAN-MAR CT volumes generated in a short time were closer to the Reference CT volumes than the Water and Artifacts CT volumes. The observed dosimetric differences compared to the reference plan were clinically acceptable.
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