AIMC Topic: Radiography, Thoracic
Clear Filters Showing 11 to 20 of 591 articles
Artificial Intelligence Iterative Reconstruction for Dose Reduction in Pediatric Chest CT: A Clinical Assessment via Below 3 Years Patients With Congenital Heart Disease.
Journal of thoracic imaging
Jul 1, 2025
PURPOSE: To assess the performance of a newly introduced deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in reducing the dose of pediatric chest CT by using the image data of below 3-y...
Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray.
PloS one
Jun 25, 2025
Thoracic diseases, including pneumonia, tuberculosis, lung cancer, and others, pose significant health risks and require timely and accurate diagnosis to ensure proper treatment. Thus, in this research, a model for thorax disease classification using...
Deep Learning-enhanced Opportunistic Osteoporosis Screening in Ultralow-Voltage (80 kV) Chest CT: A Preliminary Study.
Academic radiology
May 2, 2025
RATIONALE AND OBJECTIVES: To explore the feasibility of deep learning (DL)-enhanced, fully automated bone mineral density (BMD) measurement using the ultralow-voltage 80 kV chest CT scans performed for lung cancer screening.
Detection of Pulmonary Nodules on Ultra-low Dose Chest Computed Tomography With Deep-learning Image Reconstruction Algorithm.
Journal of thoracic imaging
May 1, 2025
PURPOSE: To evaluate the accuracy of ultra-low dose (ULD) chest computed tomography (CT), with a radiation exposure equivalent to a 2-view chest x-ray, for pulmonary nodule detection using deep learning image reconstruction (DLIR).
Cross-Sectional Studies
Male
Middle Aged
Lung Neoplasms
Humans
Multiple Pulmonary Nodules
Lung
Algorithms
Deep Learning
Radiography, Thoracic
Prospective Studies
Aged, 80 and over
Adult
Solitary Pulmonary Nodule
Sensitivity and Specificity
Tomography, X-Ray Computed
Radiographic Image Interpretation, Computer-Assisted
Female
Radiation Dosage
Aged
Deep learning based dual stage model for accurate nasogastric tube positioning in chest radiographs.
Scientific reports
Apr 25, 2025
Accurate placement of nasogastric tubes (NGTs) is crucial for ensuring patient safety and effective treatment. Traditional methods relying on manual inspection are susceptible to human error, highlighting the need for innovative solutions. This study...
Reduction of radiation exposure in chest radiography using deep learning-based noise reduction processing: A phantom and retrospective clinical study.
Radiography (London, England : 1995)
Apr 24, 2025
INTRODUCTION: Intelligent noise reduction (INR), a deep learning-based noise reduction developed by Canon, is used in planar radiography to improve image quality and reduce patient exposure dose. This study aimed to evaluate the reduction of patient ...
Reconstruction-based approach for chest X-ray image segmentation and enhanced multi-label chest disease classification.
Artificial intelligence in medicine
Apr 23, 2025
U-Net is a commonly used model for medical image segmentation. However, when applied to chest X-ray images that show pathologies, it often fails to include these critical pathological areas in the generated masks. To address this limitation, in our s...
EffiCOVID-net: A highly efficient convolutional neural network for COVID-19 diagnosis using chest X-ray imaging.
Methods (San Diego, Calif.)
Apr 17, 2025
The global COVID-19 pandemic has drastically affected daily life, emphasizing the urgent need for early and accurate detection to provide adequate medical treatment, especially with limited antiviral options. Chest X-ray imaging has proven crucial fo...
Tuberculosis detection using few shot learning.
Scientific reports
Apr 16, 2025
Tuberculosis (TB), a contagious disease, significantly affects lungs functioning. Amongst multiple detection methodologies, Chest X-ray analysis is considered the most effective methodology. Traditional Deep Learning methodologies have shown good res...
An artificial intelligence model for predicting an appropriate mAs with target exposure indicator for chest digital radiography.
Scientific reports
Apr 8, 2025
In digital radiography, image quality is synergistically affected by anatomy-specific examinations, exposure factors, body parameters, detector types, and vendors/systems. However, estimating appropriate exposure factors before radiography with optim...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32006
- Neural Networks, Computer 30221
- Algorithms 27397
- Deep Learning 26901
- Artificial Intelligence 24835
- Robotics 13387
- Image Processing, Computer-Assisted 9735
- Retrospective Studies 9342
- Magnetic Resonance Imaging 6346
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4865
- Support Vector Machine 4769
- Computational Biology 4332
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6775
- Sensors (Basel, Switzerland) 4794
- PloS one 4200
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1064
- Nature communications 1044
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 873
- Journal of medical Internet research 861
- Briefings in bioinformatics 853