Deep learning for abdominal adipose tissue segmentation with few labelled samples

2021 ◽  
Author(s):  
Zheng Wang ◽  
Alphonse Houssou Hounye ◽  
Jianglin Zhang ◽  
Muzhou Hou ◽  
Min Qi
Keyword(s):  
Adipose Tissue ◽  
Deep Learning ◽  
Tissue Segmentation ◽  
Abdominal Adipose Tissue

scholarly journals FatSegNet: A fully automated deep learning pipeline for adipose tissue segmentation on abdominal dixon MRI

2019 ◽  
Vol 83 (4) ◽  
pp. 1471-1483 ◽  
Author(s):  
Santiago Estrada ◽  
Ran Lu ◽  
Sailesh Conjeti ◽  
Ximena Orozco‐Ruiz ◽  
Joana Panos‐Willuhn ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Deep Learning ◽  
Tissue Segmentation

scholarly journals Abstract: Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI

2020 ◽  
pp. 74-74
Author(s):  
Santiago Estrada ◽  
Ran Lu ◽  
Sailesh Conjeti ◽  
Ximena Orozco ◽  
Joana Panos ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Deep Learning ◽  
Tissue Segmentation

Does intra-abdominal adipose tissue in black men determine whether NIDDM is insulin-resistant or insulin-sensitive?

Diabetes ◽  
1995 ◽  
Vol 44 (2) ◽  
pp. 141-146 ◽  
Author(s):  
M. A. Banerji ◽  
R. L. Chaiken ◽  
D. Gordon ◽  
J. G. Kral ◽  
H. E. Lebovitz
Keyword(s):  
Adipose Tissue ◽  
Black Men ◽  
Abdominal Adipose Tissue ◽  
Insulin Resistant

scholarly journals Abdominal adipose tissue components quantification in MRI as a relevant biomarker of metabolic profile

2021 ◽  
Author(s):  
Khaoula Bouazizi ◽  
Mohamed Zarai ◽  
Thomas Dietenbeck ◽  
Judith Aron-Wisnewsky ◽  
Karine Clément ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Metabolic Profile ◽  
Abdominal Adipose Tissue

scholarly journals Assessing the Role of Pericardial Fat as a Biomarker Connected to Coronary Calcification—A Deep Learning Based Approach Using Fully Automated Body Composition Analysis

2021 ◽  
Vol 10 (2) ◽  
pp. 356
Author(s):  
Lennard Kroll ◽  
Kai Nassenstein ◽  
Markus Jochims ◽  
Sven Koitka ◽  
Felix Nensa
Keyword(s):  
Adipose Tissue ◽  
Deep Learning ◽  
Coronary Artery ◽  
Cardiac Ct ◽  
Coronary Calcification ◽  
Risk Scores ◽  
Agatston Score ◽  
Composition Analysis ◽  
Significance Level ◽  
Tissue Quantification

(1) Background: Epi- and Paracardial Adipose Tissue (EAT, PAT) have been spotlighted as important biomarkers in cardiological assessment in recent years. Since biomarker quantification is an increasingly important method for clinical use, we wanted to examine fully automated EAT and PAT quantification for possible use in cardiovascular risk stratification. (2) Methods: 966 patients with intermediate Framingham risk scores for Coronary Artery Disease referred for coronary calcium scans were included in clinical routine retrospectively. The Coronary Artery Calcium Score (CACS) was extracted and tissue quantification was performed by a deep learning network. (3) Results: The Computed Tomography (CT) segmentations predicted by the network indicated no significant correlation between EAT volume and EAT radiodensity when compared to Agatston score (r = 0.18, r = −0.09). CACS 0 category patients showed significantly lower levels of total EAT and PAT volumes and higher EAT and PAT densities than CACS 1–99 category patients (p < 0.01). Notably, this difference did not reach significance regarding EAT attenuation in male patients. Women older than 50 years, thus more likely to be postmenopausal, were shown to be at higher risk of coronary calcification (p < 0.01, OR = 4.59). CACS 1–99 vs. CACS ≥100 category patients remained below significance level (EAT volume: p = 0.087, EAT attenuation: p = 0.98). (4) Conclusions: Our study proves the feasibility of a fully automated adipose tissue analysis in clinical cardiac CT and confirms in a large clinical cohort that volume and attenuation of EAT and PAT are not correlated with CACS. Broadly available deep learning based rapid and reliable tissue quantification should thus be discussed as a method to assess this biomarker as a supplementary risk predictor in cardiac CT.

scholarly journals Targeted delivery of propionate to the human colon prevents body weight and intra-abdominal adipose tissue gain in overweight adults

2014 ◽  
Vol 73 (OCE1) ◽  
Author(s):  
E. S. Chambers ◽  
A. Viardot ◽  
A. Psichas ◽  
D. J. Morrison ◽  
K. G. Murphy ◽  
...  
Keyword(s):  
Body Weight ◽  
Adipose Tissue ◽  
Targeted Delivery ◽  
Human Colon ◽  
Abdominal Adipose Tissue ◽  
Overweight Adults
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