GAN for synthesizing CT from T2-weighted MRI data towards MR-guided radiation treatment.
Amit RanjanDebanshu LalwaniRajiv MisraPublished in: Magma (New York, N.Y.) (2021)
The quantitative and qualitative comparison of this work demonstrates that deep learning-based cGAN model can be used to estimate sCT scan from a reference T2 weighted MRI scan. The overall accuracy of our proposed model outperforms different state-of-the-art deep learning-based models.
Keyphrases
- contrast enhanced
- computed tomography
- deep learning
- magnetic resonance imaging
- magnetic resonance
- dual energy
- diffusion weighted imaging
- artificial intelligence
- positron emission tomography
- convolutional neural network
- systematic review
- big data
- image quality
- high resolution
- radiation induced
- replacement therapy
- mass spectrometry
- data analysis