AIMC Topic: Contrast Media
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Generative Adversarial Network Based Contrast Enhancement: Synthetic Contrast Brain Magnetic Resonance Imaging.
Academic radiology
Dec 18, 2024
RATIONALE AND OBJECTIVES: Magnetic resonance imaging (MRI) is a vital tool for diagnosing neurological disorders, frequently utilising gadolinium-based contrast agents (GBCAs) to enhance resolution and specificity. However, GBCAs present certain risk...
Detection of late gadolinium enhancement in patients with hypertrophic cardiomyopathy using machine learning.
International journal of cardiology
Dec 18, 2024
BACKGROUND: Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in hypertrophic cardiomyopathy (HCM) typically represents myocardial fibrosis and may lead to fatal ventricular arrhythmias. However, CMR is resource-intensive and some...
Quantitative analysis of deep learning reconstruction in CT angiography: Enhancing CNR and reducing dose.
Journal of X-ray science and technology
Dec 18, 2024
BACKGROUND: Computed tomography angiography (CTA) provides significant information on image quality in vascular imaging, thus offering high-resolution images despite having the disadvantages of increased radiation doses and contrast agent-related sid...
Accurate prediction of pollution and health risks of iodinated X-ray contrast media in Taihu Lake with machine learning and revealing key environmental factors.
Water research
Dec 17, 2024
Iodinated X-ray contrast media (ICM) are commonly detected at considerable concentrations in aquatic environments. The long-term pollution trends in ICM at the whole lake/river scale have not yet been investigated; therefore, the risks associated wit...
Predicting molecular subtypes of breast cancer based on multi-parametric MRI dataset using deep learning method.
Magnetic resonance imaging
Dec 14, 2024
PURPOSE: To develop a multi-parametric MRI model for the prediction of molecular subtypes of breast cancer using five types of breast cancer preoperative MRI images.
Comparing fully automated AI body composition biomarkers at differing virtual monoenergetic levels using dual-energy CT.
Abdominal radiology (New York)
Dec 7, 2024
PURPOSE: To investigate the behavior of artificial intelligence (AI) CT-based body composition biomarkers at different virtual monoenergetic imaging (VMI) levels using dual-energy CT (DECT).
Development and Validation of a Deep Learning System to Differentiate HER2-Zero, HER2-Low, and HER2-Positive Breast Cancer Based on Dynamic Contrast-Enhanced MRI.
Journal of magnetic resonance imaging : JMRI
Dec 6, 2024
BACKGROUND: Previous studies explored MRI-based radiomic features for differentiating between human epidermal growth factor receptor 2 (HER2)-zero, HER2-low, and HER2-positive breast cancer, but deep learning's effectiveness is uncertain.
Deep Learning for Contrast Enhanced Mammography - A Systematic Review.
Academic radiology
Dec 5, 2024
BACKGROUND/AIM: Contrast-enhanced mammography (CEM) is a relatively novel imaging technique that enables both anatomical and functional breast imaging, with improved diagnostic performance compared to standard 2D mammography. The aim of this study is...
Leveraging a Vision Transformer Model to Improve Diagnostic Accuracy of Cardiac Amyloidosis With Cardiac Magnetic Resonance.
JACC. Cardiovascular imaging
Dec 4, 2024
BACKGROUND: Cardiac magnetic resonance (CMR) imaging is an important diagnostic tool for diagnosis of cardiac amyloidosis (CA). However, discrimination of CA from other etiologies of myocardial disease can be challenging.
Male
Middle Aged
Deep Learning
Contrast Media
Retrospective Studies
Female
Reproducibility of Results
Aged
Cardiomyopathy, Hypertrophic
Amyloidosis
Cardiomyopathies
Magnetic Resonance Imaging, Cine
Diagnosis, Differential
Predictive Value of Tests
Myocardium
Image Interpretation, Computer-Assisted
Humans
Decision Support Techniques
Reliability and quality of information provided by artificial intelligence chatbots on post-contrast acute kidney injury: an evaluation of diagnostic, preventive, and treatment guidance.
Revista da Associacao Medica Brasileira (1992)
Dec 2, 2024
OBJECTIVE: The aim of this study was to evaluate the reliability and quality of information provided by artificial intelligence chatbots regarding the diagnosis, preventive methods, and treatment of contrast-associated acute kidney injury, while also...
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