AIMC Topic: Tomography, X-Ray Computed
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Evaluation of semi-automated versus fully automated technologies for computed tomography scalable body composition analyses in patients with severe acute respiratory syndrome Coronavirus-2.
Clinical nutrition ESPEN
Jun 11, 2025
RATIONALE AND OBJECTIVES: Fully automated, artificial intelligence (AI) -based software has recently become available for scalable body composition analysis. Prior to broad application in the clinical arena, validation studies are needed. Our goal wa...
Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report.
Journal of medical Internet research
Jun 11, 2025
BACKGROUND: The rapid advancements in natural language processing, particularly the development of large language models (LLMs), have opened new avenues for managing complex clinical text data. However, the inherent complexity and specificity of medi...
Improving lung cancer diagnosis and survival prediction with deep learning and CT imaging.
PloS one
Jun 11, 2025
Lung cancer is a major cause of cancer-related deaths, and early diagnosis and treatment are crucial for improving patients' survival outcomes. In this paper, we propose to employ convolutional neural networks to model the non-linear relationship bet...
Differentiating Bacterial and Non-Bacterial Pneumonia on Chest CT Using Multi-Plane Features and Clinical Biomarkers.
Academic radiology
Jun 9, 2025
RATIONALE AND OBJECTIVES: Timely and accurate classification of bacterial pneumonia (BP) is essential for guiding antibiotic therapy. However, distinguishing BP from non-bacterial pneumonia (NBP) using computed tomography (CT) is challenging due to o...
Diagnostic accuracy of radiomics in risk stratification of gastrointestinal stromal tumors: A systematic review and meta-analysis.
European journal of radiology
Jun 7, 2025
RATIONALE AND OBJECTIVES: This systematic review and meta-analysis aimed to assess the diagnostic accuracy of radiomics in risk stratification of gastrointestinal stromal tumors (GISTs). It focused on evaluating radiomic models as a non-invasive tool...
Diffusion-based image translation model from low-dose chest CT to calcium scoring CT with random point sampling.
Computers in biology and medicine
Jun 7, 2025
BACKGROUND: Coronary artery calcium (CAC) scoring is an important method for cardiovascular risk assessment. While artificial intelligence (AI) has been applied to automate CAC scoring in calcium scoring computed tomography (CSCT), its application to...
SCAI-Net: An AI-driven framework for optimized, fast, and resource-efficient skull implant generation for cranioplasty using CT images.
Computers in biology and medicine
Jun 7, 2025
Skull damage caused by craniectomy or trauma necessitates accurate and precise Patient-Specific Implant (PSI) design to restore the cranial cavity. Conventional Computer-Aided Design (CAD)-based methods for PSI design are highly infrastructure-intens...
Preoperative Prognosis Prediction for Pathological Stage IA Lung Adenocarcinoma: 3D-Based Consolidation Tumor Ratio is Superior to 2D-Based Consolidation Tumor Ratio.
Academic radiology
Jun 6, 2025
BACKGROUND: The two-dimensional computed tomography measurement of the consolidation tumor ratio (2D-CTR) has limitations in the prognostic evaluation of early-stage lung adenocarcinoma: the measurement is subject to inter-observer variability and la...
Leveraging pulse wave signal properties for coronary artery calcification screening in CKD patients.
Computers in biology and medicine
Jun 6, 2025
BACKGROUND AND AIMS: Chronic kidney disease (CKD) patients are particularly susceptible to coronary atherosclerosis, which can be assessed using computed tomography (CT)-based coronary artery calcium (CAC) score. However, such a costly examination mi...
Inconsistency of AI in intracranial aneurysm detection with varying dose and image reconstruction.
Scientific reports
Jun 6, 2025
Scanner-related changes in data quality are common in medical imaging, yet monitoring their impact on diagnostic AI performance remains challenging. In this study, we performed standardized consistency testing of an FDA-cleared and CE-marked AI for t...
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