Automatic segmentation of whole-body adipose tissue from magnetic resonance fat fraction images based on machine learning.
Zhiming WangChuanli ChengHao PengYulong QiQian WanHongyu ZhouShaocheng QuDong LiangXin LiuHairong ZhengChao ZouPublished in: Magma (New York, N.Y.) (2021)
The proposed algorithm can reliably and automatically segment SAT and IAT from whole-body MRI PDFF images. The proposed method provides a simple and automatic tool for whole-body fat distribution analysis to explore the relationship between fat deposition and metabolic-related chronic diseases.
Keyphrases
- deep learning
- adipose tissue
- machine learning
- convolutional neural network
- magnetic resonance
- artificial intelligence
- contrast enhanced
- insulin resistance
- high fat diet
- magnetic resonance imaging
- big data
- fatty acid
- diffusion weighted imaging
- skeletal muscle
- computed tomography
- type diabetes
- optical coherence tomography