Synthesizing Quantitative T2 Maps in Right Lateral Knee Femoral Condyles from Multicontrast Anatomic Data with a Conditional Generative Adversarial Network.
Bragi SveinssonAkshay S ChaudhariBo ZhuNeha KoonjooMartin TorrianiGarry E GoldMatthew S RosenPublished in: Radiology. Artificial intelligence (2021)
With use of a neural network-based cGAN approach, it is feasible to synthesize T2 maps in femoral cartilage from anatomic MRI sequences, giving good agreement with MESE scans.See also commentary by Yi and Fritz in this issue.Keywords: Cartilage Imaging, Knee, Experimental Investigations, Quantification, Vision, Application Domain, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms© RSNA, 2021.
Keyphrases
- convolutional neural network
- deep learning
- machine learning
- neural network
- total knee arthroplasty
- big data
- artificial intelligence
- high resolution
- contrast enhanced
- knee osteoarthritis
- extracellular matrix
- anterior cruciate ligament
- anterior cruciate ligament reconstruction
- magnetic resonance imaging
- computed tomography
- electronic health record
- minimally invasive
- magnetic resonance
- photodynamic therapy
- data analysis