[HTML][HTML] Artificial intelligence and abdominal adipose tissue analysis: a literature review
Body composition imaging relies on assessment of tissues composition and distribution.
Quantitative data provided by body composition imaging analysis have been linked to …
Quantitative data provided by body composition imaging analysis have been linked to …
[HTML][HTML] The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review
Background Diabetes mellitus (DM) is a major health concern among children with the
widespread adoption of advanced technologies. However, concerns are growing about the …
widespread adoption of advanced technologies. However, concerns are growing about the …
FatSegNet: A fully automated deep learning pipeline for adipose tissue segmentation on abdominal dixon MRI
Purpose Introduce and validate a novel, fast, and fully automated deep learning pipeline
(FatSegNet) to accurately identify, segment, and quantify visceral and subcutaneous …
(FatSegNet) to accurately identify, segment, and quantify visceral and subcutaneous …
Automated deep learning–based segmentation of abdominal adipose tissue on Dixon MRI in adolescents: a prospective population-based study
BACKGROUND. The prevalence of childhood obesity has increased significantly worldwide,
highlighting a need for accurate noninvasive quantification of body fat distribution in …
highlighting a need for accurate noninvasive quantification of body fat distribution in …
Left ventricle automatic segmentation in cardiac MRI using a combined CNN and U-net approach
Cardiovascular diseases can be effectively prevented from worsening through early
diagnosis. To this end, various methods have been proposed to detect the disease source …
diagnosis. To this end, various methods have been proposed to detect the disease source …
Fully automated and standardized segmentation of adipose tissue compartments via deep learning in 3D whole-body MRI of epidemiologic cohort studies
Purpose To enable fast and reliable assessment of subcutaneous and visceral adipose
tissue compartments derived from whole-body MRI. Materials and Methods Quantification …
tissue compartments derived from whole-body MRI. Materials and Methods Quantification …
Analysis of volume and topography of adipose tissue in the trunk: Results of MRI of 11,141 participants in the German National Cohort
This research addresses the assessment of adipose tissue (AT) and spatial distribution of
visceral (VAT) and subcutaneous fat (SAT) in the trunk from standardized magnetic …
visceral (VAT) and subcutaneous fat (SAT) in the trunk from standardized magnetic …
Segmenting purple rapeseed leaves in the field from UAV RGB imagery using deep learning as an auxiliary means for nitrogen stress detection
Crop leaf purpling is a common phenotypic change when plants are subject to some biotic
and abiotic stresses during their growth. The extraction of purple leaves can monitor crop …
and abiotic stresses during their growth. The extraction of purple leaves can monitor crop …
Separation of water and fat signal in whole‐body gradient echo scans using convolutional neural networks
J Andersson, H Ahlström… - Magnetic resonance in …, 2019 - Wiley Online Library
Purpose To perform and evaluate water–fat signal separation of whole‐body gradient echo
scans using convolutional neural networks. Methods Whole‐body gradient echo scans of …
scans using convolutional neural networks. Methods Whole‐body gradient echo scans of …
A review of the application of deep learning in obesity: From early prediction aid to advanced management assistance
X Yi, Z Heyang, S Gao, M Li - … & Metabolic Syndrome: Clinical Research & …, 2024 - Elsevier
Background and aims Obesity is a chronic disease which can cause severe metabolic
disorders. Machine learning (ML) techniques, especially deep learning (DL), have proven to …
disorders. Machine learning (ML) techniques, especially deep learning (DL), have proven to …