AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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A novel hybrid deep learning framework based on biplanar X-ray radiography images for bone density prediction and classification.
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Jan 15, 2025
UNLABELLED: This study utilized deep learning for bone mineral density (BMD) prediction and classification using biplanar X-ray radiography (BPX) images from Huashan Hospital Medical Checkup Center. Results showed high accuracy and strong correlation...
Generative Adversarial Networks With Radiomics Supervision for Lung Lesion Generation.
IEEE transactions on bio-medical engineering
Jan 15, 2025
Data-driven methods for lesion generation are quickly emerging due to the need for realistic imaging targets for image quality assessment and virtual clinical trials. We proposed a generative adversarial network (GAN) architecture for conditional gen...
A novel deep learning-based pipeline architecture for pulp stone detection on panoramic radiographs.
Oral radiology
Jan 14, 2025
OBJECTIVES: Pulp stones are ectopic calcifications located in pulp tissue. The aim of this study is to introduce a novel method for detecting pulp stones on panoramic radiography images using a deep learning-based two-stage pipeline architecture.
Application of deep learning in automated localization and interpretation of coronary artery calcification in oncological PET/CT scans.
The international journal of cardiovascular imaging
Jan 13, 2025
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radia...
Vascular Calcification
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Automation
Coronary Vessels
Humans
Retrospective Studies
Female
Neoplasms
Deep Learning
Reproducibility of Results
Predictive Value of Tests
Aged
Coronary Angiography
Male
Positron Emission Tomography Computed Tomography
Middle Aged
Diagnostic accuracy in coronary CT angiography analysis: artificial intelligence versus human assessment.
Open heart
Jan 11, 2025
BACKGROUND: Visual assessment of coronary CT angiography (CCTA) is time-consuming, influenced by reader experience and prone to interobserver variability. This study evaluated a novel algorithm for coronary stenosis quantification (atherosclerosis im...
Retrospective Studies
Female
Reproducibility of Results
Aged
Male
Middle Aged
Severity of Illness Index
Predictive Value of Tests
Humans
Artificial Intelligence
Algorithms
Coronary Vessels
Computed Tomography Angiography
Coronary Stenosis
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Observer Variation
End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.
Open heart
Jan 11, 2025
PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ...
Deep learning-based image domain reconstruction enhances image quality and pulmonary nodule detection in ultralow-dose CT with adaptive statistical iterative reconstruction-V.
European radiology
Jan 10, 2025
OBJECTIVES: To evaluate the image quality and lung nodule detectability of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) post-processed using a deep learning image reconstruction (DLIR)-based image domain comp...
Patch-based feature mapping with generative adversarial networks for auxiliary hip fracture detection.
Computers in biology and medicine
Jan 10, 2025
BACKGROUND: Hip fractures are a significant public health issue, particularly among the elderly population. Pelvic radiographs (PXRs) play a crucial role in diagnosing hip fractures and are commonly used for their evaluation. Previous research has de...
Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study.
European radiology
Jan 10, 2025
OBJECTIVES: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagno...
Interpretable CT Radiomics-based Machine Learning Model for Preoperative Prediction of Ki-67 Expression in Clear Cell Renal Cell Carcinoma.
Academic radiology
Jan 9, 2025
RATIONALE AND OBJECTIVES: To develop and externally validate interpretable CT radiomics-based machine learning (ML) models for preoperative Ki-67 expression prediction in clear cell renal cell carcinoma (ccRCC).
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