ReviewComputational and mathematical methods in medicine2022
Deep Learning-Based Image Reconstruction for Different Medical Imaging Modalities.
Review in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed.
- Comparison of clinical-radiological and radiomics features for predicting pulmonary nodule malignancy in a multicenter study of mixed clinical and surveillance populations.European radiology · 2026Article
- Advances in artificial intelligence for neuroimaging.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026Review
- Fluoroscopy-Guided Motion Management in Particle Therapy: Evolution, Challenges, and AI-Enabled Opportunities.Tomography (Ann Arbor, Mich.) · 2026Review
- A fusion model of deep learning and conventional features based on computed tomography angiography of carotid plaque for predicting the risk of acute ischemic stroke.Quantitative imaging in medicine and surgery · 2026Article
- Errors in reconstruction of dichroic X-ray orientation tomography due to polarization rotation of the incident beam.Journal of synchrotron radiation · 2026Article
- Potential of Image2Image translation in reducing AI bias attributed to differences in CT reconstruction methods: proof-of-concept study on a paired dataset.Frontiers in radiology · 2026Article
- Fourier ptychography microscopy for digital pathology.Journal of microscopy · 2025Review
- Segmentation of renal vessels on non-enhanced CT images using deep learning models.Abdominal radiology (New York) · 2025Article
- Deep Learning-Enhanced T1-Weighted Imaging for Breast MRI at 1.5T.Diagnostics (Basel, Switzerland) · 2025Article
- [Advances in low-dose cone-beam computed tomography image reconstruction methods based on deep learning].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Review
- Deep learning network based on high-resolution magnetic resonance vessel wall imaging combined with attention mechanism for predicting stroke recurrence in patients with symptomatic intracranial atherosclerosis.Quantitative imaging in medicine and surgery · 2025Article
- Automated Imaging of Cataract Surgery Using Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2025Article
- Harnessing Artificial Intelligence in Obesity Research and Management: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2025Review
- Machine Learning and Deep Learning Applications in Magnetic Particle Imaging.Journal of magnetic resonance imaging : JMRI · 2025Review
- Limited-Angle Tomography Using a Neural Network as the Objective Function.International journal of biomedical research & practice · 2025Article
- Fourier convolutional decoder: reconstructing solar flare images via deep learning.Neural computing & applications · 2025Article
- Two novel deep-learning models to predict spontaneous ureteral calculi passage: Model development and validation.Current urology · 2024Article
- [A Survey of the Current Status and the Needs of Medical Imaging Technicians in China].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2024Article
- Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences.Diagnostics (Basel, Switzerland) · 2024Review
- Validation of deep learning-based CT image reconstruction for treatment planning.Scientific reports · 2023Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Image reconstruction in magnetic resonance imaging (MRI) and computed tomography (CT) is a mathematical process that generates images at many different angles around the patient. Image reconstruction has a fundamental impact on image quality. In recent years, the literature has focused on deep learning and its applications in medical imaging, particularly image reconstruction. Due to the performance of deep learning models in a wide variety of vision applications, a considerable amount of work has recently been carried out using image reconstruction in medical images. MRI and CT appear as the ultimate scientifically appropriate imaging mode for identifying and diagnosing different diseases in this ascension age of technology. This study demonstrates a number of deep learning image reconstruction approaches and a comprehensive review of the most widely used different databases. We also give the challenges and promising future directions for medical image reconstruction.
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.