ReviewFrontiers in neurology2019
Applications of Deep Learning to Neuro-Imaging Techniques.
Review in Frontiers in neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis 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
55 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Explainable AI: A review of applications to neuroimaging data.Frontiers in neuroscience · 2022Pooled it
- Shortening MRI scanning time for acute ischemic stroke: analysis of the effect of 3.0T MRI compressed sensing deep learning reconstruction.Emergency radiology · 2026Article
- Benchmarking Hybrid CNN-Transformer Versus Pure Transformer Architectures for Accelerated HyperpolarizedJournal of magnetic resonance imaging : JMRI · 2026Article
- Adaptive Riemannian optimization for multi-scale diffeomorphic matching.Nature communications · 2026Article
- GAN-MRI enhanced multi-organ MRI segmentation: a deep learning perspective.Radiological physics and technology · 2025Article
- Deep learning MRI halves scan time and preserves image quality across routine neuroradiologic examinations.Radiology advances · 2025Article
- The Classification of Metastatic Spine Cancer and Spinal Compression Fractures by Using CNN and SVM Techniques.Bioengineering (Basel, Switzerland) · 2024Article
- Deep learning reconstruction of diffusion-weighted brain MRI for evaluation of patients with acute neurologic symptoms.Scientific reports · 2024Article
- Osteoporotic vertebral compression fracture (OVCF) detection using artificial neural networks model based on the AO spine-DGOU osteoporotic fracture classification system.North American Spine Society journal · 2024Article
- Automated detection of fatal cerebral haemorrhage in postmortem CT data.International journal of legal medicine · 2024Article
- Artificial neural networks for the detection of odontoid fractures using the Konstanz Information Miner Analytics Platform.Asian spine journal · 2024Article
- Deep social neuroscience: the promise and peril of using artificial neural networks to study the social brain.Social cognitive and affective neuroscience · 2024Review
- Toward improving reproducibility in neuroimaging deep learning studies.Frontiers in neuroscience · 2024Article
- Pseudoaveraging for denoising of OCT angiography: a deep learning approach for image quality enhancement in healthy and diabetic eyes.International journal of retina and vitreous · 2023Article
- Convergence of Artificial Intelligence and Neuroscience towards the Diagnosis of Neurological Disorders-A Scoping Review.Sensors (Basel, Switzerland) · 2023Article
- A novel machine learning-based web application for field identification of infectious and inflammatory disorders of the central nervous system in cattle.Journal of veterinary internal medicine · 2023Article
- Automatic Detection, Classification, and Grading of Lumbar Intervertebral Disc Degeneration Using an Artificial Neural Network Model.Diagnostics (Basel, Switzerland) · 2023Article
- Accelerated Diffusion-Weighted MR Image Reconstruction Using Deep Neural Networks.Journal of digital imaging · 2023Article
- Machine learning approach for obstructive sleep apnea screening using brain diffusion tensor imaging.Journal of sleep research · 2023Article
- Magnetic Resonance Imaging of Primary Adult Brain Tumors: State of the Art and Future Perspectives.Biomedicines · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Many clinical applications based on deep learning and pertaining to radiology have been proposed and studied in radiology for classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. There are many other innovative applications of AI in various technical aspects of medical imaging, particularly applied to the acquisition of images, ranging from removing image artifacts, normalizing/harmonizing images, improving image quality, lowering radiation and contrast dose, and shortening the duration of imaging studies. This article will address this topic and will seek to present an overview of deep learning applied to neuroimaging techniques.
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.