AIMC Topic: Elasticity Imaging Techniques
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Diagnostic accuracy of texture analysis applied to T- and T-Relaxation maps for liver fibrosis classification via machine-learning algorithms with liver histology as reference standard.
European journal of radiology
Dec 20, 2024
OBJECTIVES: To explore texture analysis' ability on T and T relaxation maps to classify liver fibrosis into no-to-mild liver fibrosis (nmF) versus severe fibrosis (sF) group using machine learning algorithms and histology as reference standard.
Elasticity Imaging Techniques
Echo-Planar Imaging
Area Under Curve
Biopsy
Image Interpretation, Computer-Assisted
Reference Standards
Male
Middle Aged
Severity of Illness Index
ROC Curve
Magnetic Resonance Imaging
Liver
Principal Component Analysis
Liver Cirrhosis
Support Vector Machine
Retrospective Studies
Female
Aged
Adult
Humans
Ultrasound Versus Elastography in the Diagnosis of Hepatic Steatosis: Evaluation of Traditional Machine Learning Versus Deep Learning.
Sensors (Basel, Switzerland)
Nov 27, 2024
The prevalence of fatty liver disease is on the rise, posing a significant global health concern. If left untreated, it can progress into more serious liver diseases. Therefore, accurately diagnosing the condition at an early stage is essential for m...
Machine-learning methodologies to predict disease progression in chronic hepatitis B in Africa.
Hepatology communications
Nov 15, 2024
BACKGROUND: Little is known about the determinants of disease progression among African patients with chronic HBV infection.
Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease.
Renal failure
Oct 22, 2024
We developed a multimodal ultrasound (US) deep learning (DL) fusion model to automatically classify early fibrosis in patients with chronic kidney disease (CKD). This prospective study included patients with CKD who underwent continuous gray-scale US...
Machine learning-based discrimination of benign and malignant breast lesions on US: The contribution of shear-wave elastography.
European journal of radiology
Oct 18, 2024
PURPOSE: To build and validate a combined radiomics and machine learning (ML) approach using B-mode US and SWE images to differentiate benign from malignant solid breast lesions (BLs) and compare its performance with that of an expert radiologist.
Improving the diagnostic strategy for thyroid nodules: a combination of artificial intelligence-based computer-aided diagnosis system and shear wave elastography.
Endocrine
Oct 7, 2024
PURPOSE: Thyroid nodules are highly prevalent in the general population, posing a clinical challenge in accurately distinguishing between benign and malignant cases. This study aimed to investigate the diagnostic performance of different strategies, ...
SELFNet: Denoising Shear Wave Elastography Using Spatial-temporal Fourier Feature Networks.
Ultrasound in medicine & biology
Sep 23, 2024
OBJECTIVE: Ultrasound-based shear wave elastography offers estimation of tissue stiffness through analysis of the propagation of a shear wave induced by a stimulus. Displacement or velocity fields during the process can contain noise as a result of t...
Deep Learning Based Shear Wave Detection and Segmentation Tool for Use in Point-of-Care for Chronic Liver Disease Assessments.
Ultrasound in medicine & biology
Sep 6, 2024
OBJECTIVE: As metabolic dysfunction-associated steatotic liver disease (MASLD) becomes more prevalent worldwide, it is imperative to create more accurate technologies that make it easy to assess the liver in a point-of-care setting. The aim of this s...
Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks.
Ultrasound in medicine & biology
Aug 22, 2024
OBJECTIVE: A deep neural network (DNN) was trained to generate a multiparametric ultrasound (mpUS) volume from four input ultrasound-based modalities (acoustic radiation force impulse [ARFI] imaging, shear wave elasticity imaging [SWEI], quantitative...
Interpretable machine learning models based on shear-wave elastography radiomics for predicting cardiovascular disease in diabetic kidney disease patients.
Journal of diabetes investigation
Aug 22, 2024
BACKGROUND: The risk of cardiovascular complications is significantly elevated in patients with diabetic kidney disease (DKD). Recognizing the link between the progression of DKD and an increased risk of cardiovascular disease (CVD), it is crucial to...
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