Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs.
Sevgi Gokce KafaliShu-Fu ShihXinzhou LiGrace Hyun J KimTristan KellyShilpy ChowdhurySpencer LoongJeremy MoretzSamuel R BarnesZhaoping LiHolden H WuPublished in: Magma (New York, N.Y.) (2024)
ACD 3D U-Net and 3D nnU-Net can be automated tools to quantify abdominal SAT/VAT volume rapidly, accurately, and longitudinally in adults with overweight/obesity.
Keyphrases
- convolutional neural network
- deep learning
- adipose tissue
- insulin resistance
- weight loss
- contrast enhanced
- machine learning
- weight gain
- high throughput
- magnetic resonance imaging
- metabolic syndrome
- type diabetes
- magnetic resonance
- high fat diet
- physical activity
- high fat diet induced
- computed tomography
- body mass index