AIMC Topic: Adipose Tissue
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Deep Learning-Based CT Noise Reduction for Perivascular Adipose Tissue Evaluation.
Academic radiology
Jan 4, 2024
Automated Deep Learning-Based Segmentation of Abdominal Adipose Tissue on Dixon MRI in Adolescents: A Prospective Population-Based Study.
AJR. American journal of roentgenology
Aug 16, 2023
The prevalence of childhood obesity has increased significantly worldwide, highlighting a need for accurate noninvasive quantification of body fat distribution in children. The purpose of this study was to develop and test an automated deep learnin...
Athlete body fat rate monitoring and motion image simulation based on SDN data center network and sensors.
Preventive medicine
Jul 13, 2023
With the development of artificial intelligence technology, new software is also emerging in an endless stream. On the basis of sensors, the new software realizes the separation of network control layer and data layer, thereby improving network throu...
Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography: Implications for Cardiovascular Risk Prediction.
JACC. Cardiovascular imaging
Feb 8, 2023
BACKGROUND: Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CCTA). The clinical value of integrating this measurement in routine CCTA interpretation has not been ...
Identifying congenital generalized lipodystrophy using deep learning-DEEPLIPO.
Scientific reports
Feb 7, 2023
Congenital Generalized Lipodystrophy (CGL) is a rare autosomal recessive disease characterized by near complete absence of functional adipose tissue from birth. CGL diagnosis can be based on clinical data including acromegaloid features, acanthosis n...
Validity and reliability of a mobile digital imaging analysis trained by a four-compartment model.
Journal of human nutrition and dietetics : the official journal of the British Dietetic Association
Dec 7, 2022
BACKGROUND: Digital imaging analysis (DIA) estimates collected from mobile applications comprise a novel technique that can collect body composition estimates remotely without the inherent restrictions of other research-grade devices. However, the ac...
Automated volume measurement of abdominal adipose tissue from entire abdominal cavity in Dixon MR images using deep learning.
Radiological physics and technology
Nov 8, 2022
The purpose of this study was to realize an automated volume measurement of abdominal adipose tissue from the entire abdominal cavity in Dixon magnetic resonance (MR) images using deep learning. Our algorithm involves a combination of extraction of t...
Automated segmentation of five different body tissues on computed tomography using deep learning.
Medical physics
Sep 2, 2022
PURPOSE: To develop and validate a computer tool for automatic and simultaneous segmentation of five body tissues depicted on computed tomography (CT) scans: visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intermuscular adipose tiss...
Deep learning-based fully automated body composition analysis of thigh CT: comparison with DXA measurement.
European radiology
Apr 18, 2022
OBJECTIVES: To compare volumetric CT with DL-based fully automated segmentation and dual-energy X-ray absorptiometry (DXA) in the measurement of thigh tissue composition.
Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19.
Cells
Mar 18, 2022
Background: To develop a deep-learning (DL) pipeline that allowed an automated segmentation of epicardial adipose tissue (EAT) from low-dose computed tomography (LDCT) and investigate the link between EAT and COVID-19 clinical outcomes. Methods: This...
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