AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Application of a pulmonary nodule detection program using AI technology to ultra-low-dose CT: differences in detection ability among various image reconstruction methods.
Japanese journal of radiology
Aug 1, 2025
PURPOSE: This study aimed to investigate the performance of an artificial intelligence (AI)-based lung nodule detection program in ultra-low-dose CT (ULDCT) imaging, with a focus on the influence of various image reconstruction methods on detection a...
Agreement between Routine-Dose and Lower-Dose CT with and without Deep Learning-based Denoising for Active Surveillance of Solid Small Renal Masses: A Multiobserver Study.
Radiology. Imaging cancer
Jul 1, 2025
Purpose To assess the agreement between routine-dose (RD) and lower-dose (LD) contrast-enhanced CT scans, with and without Digital Imaging and Communications in Medicine-based deep learning-based denoising (DLD), in evaluating small renal masses (SRM...
Acquisition and Reconstruction Techniques for Coronary CT Angiography: Current Status and Trends over the Past Decade.
Radiographics : a review publication of the Radiological Society of North America, Inc
Jul 1, 2025
Coronary CT angiography (CCTA) has been widely used as a noninvasive modality for accurate assessment of coronary artery disease (CAD) in clinical settings. However, the following limitations of CCTA remain issues of interest: motion, stair-step, and...
Exploring best-performing radiomic features with combined multilevel discrete wavelet decompositions for multiclass COVID-19 classification using chest X-ray images.
Computers in biology and medicine
Jul 1, 2025
Discrete wavelet transforms have been applied in many machine learning models for the analysis of COVID-19; however, little is known about the impact of combined multilevel wavelet decompositions for the disease identification. This study proposes a ...
Deep Learning Image Reconstruction (DLIR) Algorithm to Maintain High Image Quality and Diagnostic Accuracy in Quadruple-low CT Angiography of Children with Pulmonary Sequestration: A Case Control Study.
Academic radiology
Jul 1, 2025
RATIONALE AND OBJECTIVES: CT angiography (CTA) is a commonly used clinical examination to detect abnormal arteries and diagnose pulmonary sequestration (PS). Reducing the radiation dose, contrast medium dosage, and injection pressure in CTA, especial...
Trustworthy AI for stage IV non-small cell lung cancer: Automatic segmentation and uncertainty quantification.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 1, 2025
Accurate segmentation of lung tumors is essential for advancing personalized medicine in non-small cell lung cancer (NSCLC). However, stage IV NSCLC presents significant challenges due to heterogeneous tumor morphology and the presence of associated ...
Automated vertebrae identification and segmentation with structural uncertainty analysis in longitudinal CT scans of patients with multiple myeloma.
European journal of radiology
Jul 1, 2025
OBJECTIVES: Optimize deep learning-based vertebrae segmentation in longitudinal CT scans of multiple myeloma patients using structural uncertainty analysis.
Quantitative CT biomarkers for renal cell carcinoma subtype differentiation: a comparison of DECT, PCT, and CT texture analysis.
The British journal of radiology
Jul 1, 2025
OBJECTIVE: To evaluate and compare the diagnostic performance of CT texture analysis (CTTA), perfusion CT (PCT), and dual-energy CT (DECT) in distinguishing between clear-cell renal cell carcinoma (ccRCC) and non-ccRCC.
Multitask Deep Learning for Automated Detection of Endoleak at Digital Subtraction Angiography during Endovascular Aneurysm Repair.
Radiology. Artificial intelligence
Jul 1, 2025
Purpose To develop and evaluate a novel multitask deep learning framework for automated detection and localization of endoleaks at aortic digital subtraction angiography (DSA) performed during real-world endovascular aneurysm repair (EVAR) procedures...
Radiation and contrast dose reduction in coronary CT angiography for slender patients with 70 kV tube voltage and deep learning image reconstruction.
The British journal of radiology
Jul 1, 2025
OBJECTIVE: To evaluate the radiation and contrast dose reduction potential of combining 70 kV with deep learning image reconstruction (DLIR) in coronary computed tomography angiography (CCTA) for slender patients with body-mass-index (BMI) ≤25 kg/m2.
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