AIMC Topic: Adipose Tissue

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Adaptive Fruitfly Based Modified Region Growing Algorithm for Cardiac Fat Segmentation Using Optimal Neural Network.

Journal of medical systems
Epicardial adipose tissue is a visceral fat that has remained an entity of concern for decades owing to its high correlation with coronary heart disease. It continues to stump medical practitioners on the pretext of its relevance with pericardial fat...

Robust water-fat separation for multi-echo gradient-recalled echo sequence using convolutional neural network.

Magnetic resonance in medicine
PURPOSE: To accurately separate water and fat signals for bipolar multi-echo gradient-recalled echo sequence using a convolutional neural network (CNN).

An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets.

Medical physics
PURPOSE: Accurate segmentation of the breast is required for breast density estimation and the assessment of background parenchymal enhancement, both of which have been shown to be related to breast cancer risk. The MRI breast segmentation task is ch...

Water-fat separation and parameter mapping in cardiac MRI via deep learning with a convolutional neural network.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Water-fat separation is a postprocessing technique most commonly applied to multiple-gradient-echo magnetic resonance (MR) images to identify fat, provide images with fat suppression, and to measure fat tissue concentration. Recently, Num...

Deep learning-based quantification of abdominal fat on magnetic resonance images.

PloS one
Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, cardiovascular diseases, and cancer. Magnetic resonance imaging (MRI) is an accurate method for determination of body fat volume and distribution. How...

An unsupervised automatic segmentation algorithm for breast tissue classification of dedicated breast computed tomography images.

Medical physics
PURPOSE: To develop and evaluate a new automatic classification algorithm to identify voxels containing skin, vasculature, adipose, and fibroglandular tissue in dedicated breast CT images.

Prediction of pork loin quality using online computer vision system and artificial intelligence model.

Meat science
The objective of this project was to develop a computer vision system (CVS) for objective measurement of pork loin under industry speed requirement. Color images of pork loin samples were acquired using a CVS. Subjective color and marbling scores wer...

Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT.

IEEE transactions on medical imaging
Epicardial adipose tissue (EAT) is a visceral fat deposit related to coronary artery disease. Fully automated quantification of EAT volume in clinical routine could be a timesaving and reliable tool for cardiovascular risk assessment. We propose a ne...