ArticleFrontiers in bioengineering and biotechnology2018
Exploring the Potential of Generative Adversarial Networks for Synthesizing Radiological Images of the Spine to be Used in
Article in Frontiers in bioengineering and biotechnology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
13 citing papers in PubMed, 33 citations in OpenAlex.
- Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis.European radiology experimental · 2025Article
- A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology.Current research in toxicology · 2025Review
- Generating Synthesized Fluorescein Angiography Images From Color Fundus Images by Generative Adversarial Networks for Macular Edema Assessment.Translational vision science & technology · 2024Article
- Image factory: A method for synthesizing novel CT images with anatomical guidance.Medical physics · 2024Article
- A dual analysis of bougie and stylet development trend and impact of Chinese regulations on medical devices innovation.American journal of translational research · 2024Review
- AI musculoskeletal clinical applications: how can AI increase my day-to-day efficiency?Skeletal radiology · 2022Review
- Short-Axis PET Image Quality Improvement by Attention CycleGAN Using Total-Body PET.Journal of healthcare engineering · 2022Article
- Local Style Preservation in Improved GAN-Driven Synthetic Image Generation for Endoscopic Tool Segmentation.Sensors (Basel, Switzerland) · 2021Article
- 2D-3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks.Scientific reports · 2021Article
- Deep Generative Adversarial Networks: Applications in Musculoskeletal Imaging.Radiology. Artificial intelligence · 2021Review
- Variational Autoencoder Modular Bayesian Networks for Simulation of Heterogeneous Clinical Study Data.Frontiers in big data · 2020Article
- CycleGAN for style transfer in X-ray angiography.International journal of computer assisted radiology and surgery · 2019Article
- Generative models: an upcoming innovation in musculoskeletal radiology? A preliminary test in spine imaging.European radiology experimental · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
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.