AIMC Topic: Liver
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Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints.
Scientific reports
Jan 15, 2025
Accurately extracting organs from medical images provides radiologist with more comprehensive evidences to clinical diagnose, which offers up a higher accuracy and efficiency. However, the key to achieving accurate segmentation lies in abundant clues...
Toward efficient slide-level grading of liver biopsy via explainable deep learning framework.
Medical & biological engineering & computing
Jan 13, 2025
In the context of chronic liver diseases, where variability in progression necessitates early and precise diagnosis, this study addresses the limitations of traditional histological analysis and the shortcomings of existing deep learning approaches. ...
Multi-site, multi-vendor development and validation of a deep learning model for liver stiffness prediction using abdominal biparametric MRI.
European radiology
Jan 9, 2025
BACKGROUND: Chronic liver disease (CLD) is a substantial cause of morbidity and mortality worldwide. Liver stiffness, as measured by MR elastography (MRE), is well-accepted as a surrogate marker of liver fibrosis.
HepNet: Deep Neural Network for Classification of Early-Stage Hepatic Steatosis Using Microwave Signals.
IEEE journal of biomedical and health informatics
Jan 7, 2025
Hepatic steatosis, a key factor in chronic liver diseases, is difficult to diagnose early. This study introduces a classifier for hepatic steatosis using microwave technology, validated through clinical trials. Our method uses microwave signals and d...
Deep denoising approach to improve shear wave phase velocity map reconstruction in ultrasound elastography.
Medical physics
Dec 23, 2024
BACKGROUND: Measurement noise often leads to inaccurate shear wave phase velocity estimation in ultrasound shear wave elastography. Filtering techniques are commonly used for denoising the shear wavefields. However, these filters are often not suffic...
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.
Principal Component Analysis
Area Under Curve
Biopsy
Image Interpretation, Computer-Assisted
Reference Standards
Elasticity Imaging Techniques
Female
Echo-Planar Imaging
Aged
Liver Cirrhosis
Adult
Support Vector Machine
Male
Humans
Magnetic Resonance Imaging
Retrospective Studies
Liver
Middle Aged
Severity of Illness Index
ROC Curve
Effects of prolonged oxytetracycline supplementation on freshwater stinging catfish (): a multi-biomarker approach.
Frontiers in immunology
Dec 19, 2024
BACKGROUND: Aquaculture systems that sporadically depend on antibiotics can contribute to the development of adverse effects on the fish, microbial flora and the environment. This study sought to investigate the impacts of extended oxytetracycline su...
Quantitative fibrosis identifies biliary tract involvement and is associated with outcomes in pediatric autoimmune liver disease.
Hepatology communications
Dec 11, 2024
BACKGROUND: Children with autoimmune liver disease (AILD) may develop fibrosis-related complications necessitating a liver transplant. We hypothesize that tissue-based analysis of liver fibrosis by second harmonic generation (SHG) microscopy with art...
Breath-hold diffusion-weighted MR imaging (DWI) using deep learning reconstruction: Comparison with navigator triggered DWI in patients with malignant liver tumors.
Radiography (London, England : 1995)
Dec 11, 2024
INTRODUCTION: This study investigated the feasibility of single breath-hold (BH) diffusion-weighted MR imaging (DWI) using deep learning reconstruction (DLR) compared to navigator triggered (NT) DWI in patients with malignant liver tumors.
A machine learning model for predicting abnormal liver function induced by a Chinese herbal medicine preparation (Zhengqing Fengtongning) in patients with rheumatoid arthritis based on real-world study.
Journal of integrative medicine
Dec 6, 2024
OBJECTIVE: Rheumatoid arthritis (RA) is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients' quality of life. Zhengqing Fengtongning (ZF) is a traditional Chinese medicine preparation used to treat ...
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