AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
Clear Filters Showing 1071 to 1080 of 1324 articles
A Deep Learning Model for Comprehensive Automated Bone Lesion Detection and Classification on Staging Computed Tomography Scans.
Academic radiology
Sep 1, 2025
RATIONALE AND OBJECTIVES: A common site of metastases for a variety of cancers is the bone, which is challenging and time consuming to review and important for cancer staging. Here, we developed a deep learning approach for detection and classificati...
An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels.
Artificial intelligence in medicine
Sep 1, 2025
The diagnostic accuracy and subjectivity of existing Knee Osteoarthritis (OA) ordinal grading systems has been a subject of on-going debate and concern. Existing automated solutions are trained to emulate these imperfect systems, whilst also being re...
Deep Learning-Based Multimodal Feature Interaction-Guided Fusion: Enhancing the Evaluation of EGFR in Advanced Lung Adenocarcinoma.
Academic radiology
Sep 1, 2025
RATIONALE AND OBJECTIVES: The aim of this study is to develop a deep learning-based multimodal feature interaction-guided fusion (DL-MFIF) framework that integrates macroscopic information from computed tomography (CT) images with microscopic informa...
Detection, Classification, and Segmentation of Rib Fractures From CT Data Using Deep Learning Models: A Review of Literature and Pooled Analysis.
Journal of thoracic imaging
Sep 1, 2025
PURPOSE: Trauma-induced rib fractures are common injuries. The gold standard for diagnosing rib fractures is computed tomography (CT), but the sensitivity in the acute setting is low, and interpreting CT slices is labor-intensive. This has led to the...
Real-world Evaluation of Computer-aided Pulmonary Nodule Detection Software Sensitivity and False Positive Rate.
Journal of thoracic imaging
Sep 1, 2025
PURPOSE: Evaluate the false positive rate (FPR) of nodule detection software in real-world use.
Impact of Deep Learning-Based Image Conversion on Fully Automated Coronary Artery Calcium Scoring Using Thin-Slice, Sharp-Kernel, Non-Gated, Low-Dose Chest CT Scans: A Multi-Center Study.
Korean journal of radiology
Aug 1, 2025
OBJECTIVE: To evaluate the impact of deep learning-based image conversion on the accuracy of automated coronary artery calcium quantification using thin-slice, sharp-kernel, non-gated, low-dose chest computed tomography (LDCT) images collected from m...
Deep-learning based automated pancreas segmentation on CT scans of chronic pancreatitis patients.
European journal of radiology
Aug 1, 2025
OBJECTIVES: This study aimed to develop an artificial intelligence (AI)-based segmentation model for accurate delineation of the complex pancreas in patients with chronic pancreatitis (CP) using computer tomography (CT) scans obtained during routine ...
Improving image quality and diagnostic performance using deep learning image reconstruction in 100-kVp CT enterography for patients with wide-range body mass index.
European journal of radiology
Aug 1, 2025
OBJECTIVE: To assess the clinical value of the deep learning image reconstruction (DLIR) algorithm compared with conventional adaptive statistical iterative reconstruction-Veo (ASiR-V) in image quality, diagnostic confidence, and intestinal lesion de...
Humans
Middle Aged
Algorithms
Aged, 80 and over
Retrospective Studies
Deep Learning
Intestinal Diseases
Adult
Body Mass Index
Tomography, X-Ray Computed
Sensitivity and Specificity
Radiographic Image Interpretation, Computer-Assisted
Quality Improvement
Female
Male
Signal-To-Noise Ratio
Reproducibility of Results
Aged
Application of Quantitative CT and Machine Learning in the Evaluation and Diagnosis of Polymyositis/Dermatomyositis-Associated Interstitial Lung Disease.
Academic radiology
Aug 1, 2025
RATIONALE AND OBJECTIVES: To investigate lung changes in patients with polymyositis/dermatomyositis-associated interstitial lung disease (PM/DM-ILD) using quantitative CT and to construct a diagnostic model to evaluate the application of quantitative...
Diagnosis of thyroid cartilage invasion by laryngeal and hypopharyngeal cancers based on CT with deep learning.
European journal of radiology
Aug 1, 2025
OBJECTIVES: To develop a convolutional neural network (CNN) model to diagnose thyroid cartilage invasion by laryngeal and hypopharyngeal cancers observed on computed tomography (CT) images and evaluate the model's diagnostic performance.
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 32531
- Neural Networks, Computer 30499
- Algorithms 27741
- Deep Learning 27298
- Artificial Intelligence 25221
- Robotics 13430
- Image Processing, Computer-Assisted 9890
- Retrospective Studies 9535
- Magnetic Resonance Imaging 6484
- Reproducibility of Results 5746
- Tomography, X-Ray Computed 4962
- Support Vector Machine 4812
- Computational Biology 4396
- Brain 4188
- Computer Simulation 3963
Recent Journals
- Scientific reports 7012
- Sensors (Basel, Switzerland) 4794
- PloS one 4314
- Neural networks : the official journal of the International Neural Network Society 3035
- Computers in biology and medicine 2040
- Computational intelligence and neuroscience 1931
- 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 1395
- IEEE journal of biomedical and health informatics 1197
- Journal of chemical information and modeling 1087
- Nature communications 1071
- Computer methods and programs in biomedicine 895
- Journal of medical Internet research 879
- Bioinformatics (Oxford, England) 879
- IEEE transactions on neural networks and learning systems 859