AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Enhancing quantitative coronary angiography (QCA) with advanced artificial intelligence: comparison with manual QCA and visual estimation.
The international journal of cardiovascular imaging
Jan 29, 2025
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MP...
Intraindividual Comparison of Image Quality Between Low-Dose and Ultra-Low-Dose Abdominal CT With Deep Learning Reconstruction and Standard-Dose Abdominal CT Using Dual-Split Scan.
Investigative radiology
Jan 28, 2025
OBJECTIVE: The aim of this study was to intraindividually compare the conspicuity of focal liver lesions (FLLs) between low- and ultra-low-dose computed tomography (CT) with deep learning reconstruction (DLR) and standard-dose CT with model-based ite...
Advancing lung cancer diagnosis: Combining 3D auto-encoders and attention mechanisms for CT scan analysis.
Journal of X-ray science and technology
Jan 28, 2025
ObjectiveThe goal of this study is to assess the effectiveness of a hybrid deep learning model that combines 3D Auto-encoders with attention mechanisms to detect lung cancer early from CT scan images. The study aims to improve diagnostic accuracy, se...
Automatic segmentation and volumetric analysis of intracranial hemorrhages in brain CT images.
European journal of radiology
Jan 27, 2025
BACKGROUND: Intracranial hemorrhages (ICH) are life-threatening conditions that require rapid detection and precise subtype classification. Automated segmentation and volumetric analysis using deep learning can enhance clinical decision-making.
Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.
Tomography (Ann Arbor, Mich.)
Jan 27, 2025
BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thick...
Multistage deep learning methods for automating radiographic sharp score prediction in rheumatoid arthritis.
Scientific reports
Jan 27, 2025
The Sharp-van der Heijde score (SvH) is crucial for assessing joint damage in rheumatoid arthritis (RA) through radiographic images. However, manual scoring is time-consuming and subject to variability. This study proposes a multistage deep learning ...
Automated spinopelvic measurements on radiographs with artificial intelligence: a multi-reader study.
La Radiologia medica
Jan 26, 2025
PURPOSE: To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.
Effect of artificial intelligence-aided differentiation of adenomatous and non-adenomatous colorectal polyps at CT colonography on radiologists' therapy management.
European radiology
Jan 25, 2025
OBJECTIVES: Adenomatous colorectal polyps require endoscopic resection, as opposed to non-adenomatous hyperplastic colorectal polyps. This study aims to evaluate the effect of artificial intelligence (AI)-assisted differentiation of adenomatous and n...
Aged
Aged, 80 and over
Adult
Sensitivity and Specificity
Humans
Artificial Intelligence
Retrospective Studies
Female
Radiologists
Radiographic Image Interpretation, Computer-Assisted
Colorectal Neoplasms
Colonic Polyps
Male
Adenomatous Polyps
Middle Aged
Colonography, Computed Tomographic
Diagnosis, Differential
A deep learning pipeline for systematic and accurate vertebral fracture reporting in computed tomography.
Clinical radiology
Jan 25, 2025
AIM: Spine fractures are a frequent and relevant diagnosis, but systematic documentation is time-consuming and sometimes overlooked. A deep learning pipeline for opportunistic fracture detection in computed tomography (CT) spine images of varying fie...
AI-assisted radiologists vs. standard double reading for rib fracture detection on CT images: A real-world clinical study.
PloS one
Jan 24, 2025
To evaluate the diagnostic accuracy of artificial intelligence (AI) assisted radiologists and standard double-reading in real-world clinical settings for rib fractures (RFs) detection on CT images. This study included 243 consecutive chest trauma pat...
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