AIMC Topic: Contrast Media
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Convolutional Neural Networks to Study Contrast-Enhanced Magnetic Resonance Imaging-Based Skeletal Calf Muscle Perfusion in Peripheral Artery Disease.
The American journal of cardiology
Apr 3, 2024
Peripheral artery disease (PAD) is associated with impaired blood flow in the lower extremities and histopathologic changes of the skeletal calf muscles, resulting in abnormal microvascular perfusion. We studied the use of convolution neural networks...
Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning.
European radiology
Mar 27, 2024
BACKGROUND: Accurate mortality risk quantification is crucial for the management of hepatocellular carcinoma (HCC); however, most scoring systems are subjective.
Radiomics-based machine learning in the differentiation of benign and malignant bowel wall thickening radiomics in bowel wall thickening.
Japanese journal of radiology
Mar 27, 2024
PURPOSE: To distinguish malignant and benign bowel wall thickening (BWT) by using computed tomography (CT) texture features based on machine learning (ML) models and to compare its success with the clinical model and combined model.
Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Mar 24, 2024
BACKGROUND: Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images ...
Databases, Factual
Female
Reproducibility of Results
Aged
Deep Learning
Contrast Media
Magnetic Resonance Imaging
Male
Middle Aged
Humans
Quality Assurance, Health Care
Predictive Value of Tests
Observer Variation
Myocardium
Magnetic Resonance Imaging, Cine
Heart Diseases
Image Interpretation, Computer-Assisted
Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI.
Abdominal radiology (New York)
Mar 21, 2024
PURPOSE: To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arterial-phase magnetic resonance imaging (MA-MRI) for small hypervascular hepatic masses in patients who underwent gadoxetic acid-enhanced liver MRI.
Malignancy diagnosis of liver lesion in contrast enhanced ultrasound using an end-to-end method based on deep learning.
BMC medical imaging
Mar 21, 2024
BACKGROUND: Contrast-enhanced ultrasound (CEUS) is considered as an efficient tool for focal liver lesion characterization, given it allows real-time scanning and provides dynamic tissue perfusion information. An accurate diagnosis of liver lesions w...
Unpaired deep learning for pharmacokinetic parameter estimation from dynamic contrast-enhanced MRI without AIF measurements.
NeuroImage
Mar 20, 2024
DCE-MRI provides information about vascular permeability and tissue perfusion through the acquisition of pharmacokinetic parameters. However, traditional methods for estimating these pharmacokinetic parameters involve fitting tracer kinetic models, w...
Enhancing gadoxetic acid-enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques.
European radiology
Mar 16, 2024
OBJECTIVE: To investigate whether a deep learning (DL) controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE) technique can improve image quality, lesion conspicuity,...
Machine Learning Radiomics-Based Prediction of Non-sentinel Lymph Node Metastasis in Chinese Breast Cancer Patients with 1-2 Positive Sentinel Lymph Nodes: A Multicenter Study.
Academic radiology
Mar 15, 2024
RATIONALE AND OBJECTIVES: This study aimed to construct a machine learning radiomics-based model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images to evaluate non-sentinel lymph node (NSLN) metastasis in Chinese breast cance...
Combination of DCE-MRI and NME-DWI via Deep Neural Network for Predicting Breast Cancer Molecular Subtypes.
Clinical breast cancer
Mar 13, 2024
BACKGROUND: To explore whether the combination of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and nonmono-exponential (NME) model-based diffusion-weighted imaging (DWI) via deep neural network (DNN) can improve the prediction of ...
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