ArticleTechnology in cancer research & treatment
Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Deep learning for head and neck radiation dose prediction: a systematic review and meta-analysis.Scientific reports · 2025Pooled it
- A systematic literature review: deep learning techniques for synthetic medical image generation and their applications in radiotherapy.Frontiers in radiology · 2024Pooled it
- Deep learning methods for enhancing cone-beam CT image quality toward adaptive radiation therapy: A systematic review.Medical physics · 2022Pooled it
- Deep learning-based metal artifact reduction in CT for head and neck radiotherapy.Physics and imaging in radiation oncology · 2026Review
- Deep learning-based multi-modality image conversion for evaluating dose calculation and position correction accuracy in image-guided radiation therapy.Radiological physics and technology · 2026Article
- Equivariant conditional diffusion model for head and neck CT image synthesis from CBCT.Medical physics · 2026Article
- Synthetic CT generation from cone-beam CT using deep learning for head-and-neck adaptive radiotherapy.Physics and imaging in radiation oncology · 2026Article
- Self-learning GAN based synthetic CT generation: unlocking CBCT-based adaptive radiotherapy.Frontiers in oncology · 2026Article
- Cone-beam computed tomography (CBCT) image-quality improvement using a denoising diffusion probabilistic model conditioned by pseudo-CBCT of pelvic regions.Radiological physics and technology · 2025Article
- Advancements in synthetic CT generation from MRI: A review of techniques, and trends in radiation therapy planning.Journal of applied clinical medical physics · 2024Review
- Proton dose calculation on cone-beam computed tomography using unsupervised 3D deep learning networks.Physics and imaging in radiation oncology · 2024Article
- Supervised deep learning-based synthetic computed tomography from kilovoltage cone-beam computed tomography images for adaptive radiation therapy in head and neck cancer.Radiation oncology journal · 2024Article
- Artificial intelligence in interventional radiology: state of the art.European radiology experimental · 2024Review
- Article
- Generating synthetic images from cone beam computed tomography using self-attention residual UNet for head and neck radiotherapy.Physics and imaging in radiation oncology · 2023Article
- Improving synthetic CT accuracy by combining the benefits of multiple normalized preprocesses.Journal of applied clinical medical physics · 2023Article
- CBCT-to-CT Translation Using Registration-Based Generative Adversarial Networks in Patients with Head and Neck Cancer.Cancers · 2023Article
- Patient-specific synthetic magnetic resonance imaging generation from cone beam computed tomography for image guidance in liver stereotactic body radiation therapy.Precision radiation oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.