AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Application of machine learning in the preoperative radiomic diagnosis of ameloblastoma and odontogenic keratocyst based on cone-beam CT.
Dento maxillo facial radiology
Jun 28, 2024
OBJECTIVES: Preoperative diagnosis of oral ameloblastoma (AME) and odontogenic keratocyst (OKC) has been a challenge in dentistry. This study uses radiomics approaches and machine learning (ML) algorithms to characterize cone-beam CT (CBCT) image fea...
How Artificial Intelligence Will Enhance Imaging Access and Analysis.
JAMA
Jun 18, 2024
Improved stent sharpness evaluation with super-resolution deep learning reconstruction in coronary CT angiography.
The British journal of radiology
Jun 18, 2024
OBJECTIVES: This study aimed to assess the impact of super-resolution deep learning reconstruction (SR-DLR) on coronary CT angiography (CCTA) image quality and blooming artifacts from coronary artery stents in comparison to conventional methods, incl...
Revolutionizing aortic aneurysm assessment with artificial intelligence.
Journal of vascular surgery
Jun 1, 2024
Patient Characteristics Impact Performance of AI Algorithm in Interpreting Negative Screening Digital Breast Tomosynthesis Studies.
Radiology
May 1, 2024
Background Artificial intelligence (AI) is increasingly used to manage radiologists' workloads. The impact of patient characteristics on AI performance has not been well studied. Purpose To understand the impact of patient characteristics (race and e...
AI Improves Cancer Detection and Reading Time of Digital Breast Tomosynthesis.
Radiology. Artificial intelligence
May 1, 2024
Deep Learning Assessment of Small Renal Masses at Contrast-enhanced Multiphase CT.
Radiology
May 1, 2024
Background Accurate characterization of suspicious small renal masses is crucial for optimized management. Deep learning (DL) algorithms may assist with this effort. Purpose To develop and validate a DL algorithm for identifying benign small renal ma...
Enhancing AI-assisted Interpretation of Chest Radiographs: A Critical Analysis of Methods and Applicability.
Radiology
May 1, 2024
A Semiautonomous Deep Learning System to Reduce False Positives in Screening Mammography.
Radiology. Artificial intelligence
May 1, 2024
Purpose To evaluate the ability of a semiautonomous artificial intelligence (AI) model to identify screening mammograms not suspicious for breast cancer and reduce the number of false-positive examinations. Materials and Methods The deep learning alg...
Performance of an Artificial Intelligence System for Breast Cancer Detection on Screening Mammograms from BreastScreen Norway.
Radiology. Artificial intelligence
May 1, 2024
Purpose To explore the stand-alone breast cancer detection performance, at different risk score thresholds, of a commercially available artificial intelligence (AI) system. Materials and Methods This retrospective study included information from 661 ...
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