Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.
Fang LiuZhaoye ZhouHyungseok JangAlexey SamsonovGengyan ZhaoRichard KijowskiPublished in: Magnetic resonance in medicine (2017)
The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Keyphrases
- convolutional neural network
- deep learning
- magnetic resonance
- magnetic resonance imaging
- high resolution
- contrast enhanced
- computed tomography
- bone mineral density
- machine learning
- extracellular matrix
- risk assessment
- body composition
- postmenopausal women
- loop mediated isothermal amplification
- bone loss
- diffusion weighted imaging
- sensitive detection