E³ 220 - Artificial intelligence for image reconstruction: towards deep imaging?
Lectures
E3 220 - A. Deep learning for MRI reconstruction
14:18K. Hammernik, London / UK
Learning Objectives
1. To show how with deep learning we can learn the entire MRI reconstruction procedure.
2. To understand the advantages and disadvantages of using deep learning in MRI reconstruction.
3. To show the application of deep learning in the reconstruction of MRI musculoskeletal images.
E3 220 - B. Deep learning in cardiovascular MRI
14:28D. Rueckert, London / UK
Learning Objectives
1. To understand how MRI acquisition time can be reduced with deep learning.
2. To understand potential artefacts related to deep learning based image reconstruction.
3. To show applications of deep learning in the reconstruction of cardiovascular MRI data.
E³ 220 - C. Deep learning in CT imaging
14:24M. Prokop, Nijmegen / NL
Learning Objectives
1. To learn how deep learning can be used to improve CT image quality.
2. To understand how deep learning can be used to speed up CT image acquisition.
3. To learn about clinical applications of deep learning based CT reconstruction.
2. To understand the advantages and disadvantages of using deep learning in MRI reconstruction.
3. To show the application of deep learning in the reconstruction of MRI musculoskeletal images.
2. To understand potential artefacts related to deep learning based image reconstruction.
3. To show applications of deep learning in the reconstruction of cardiovascular MRI data.
2. To understand how deep learning can be used to speed up CT image acquisition.
3. To learn about clinical applications of deep learning based CT reconstruction.