E³ - Advanced Courses

E³ 222 - Artificial intelligence for image reconstruction: towards deep imaging?

Lectures

1
E³ 222 - A. Deep learning for MRI reconstruction

E³ 222 - A. Deep learning for MRI reconstruction

18:43K. Hammernik, London / UK

Learning Objectives
1. To demonstrate 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 demonstrate the application of deep learning in the reconstruction of MRI musculoskeletal images.

2
E³ 222 - B. Deep learning in cardic MRI acquisition and reconstruction

E³ 222 - B. Deep learning in cardic MRI acquisition and reconstruction

18:16D. Rueckert, London / UK

Learning Objectives
1. To understand how MRI acquisition time can be reduced with deep learning.
2. To understand the potential artefacts related to deep learning-based image reconstruction.
3. To demonstrate the applications of deep learning in the reconstruction of cardiovascular MRI data.

3
E³ 222 - C. Deep learning in CT image acquisition and reconstruction

E³ 222 - C. Deep learning in CT image acquisition and reconstruction

20:18M. Prokop, Nijmegen / Netherlands

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.

E³ 222-1
A. Deep learning for MRI reconstruction
Kerstin Hammernik, Garching bei München / Germany
Learning Objectives
1. To demonstrate 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 demonstrate the application of deep learning in the reconstruction of MRI musculoskeletal images.
E³ 222-2
B. Deep learning in cardic MRI acquisition and reconstruction
Daniel Rueckert, London / United Kingdom
Learning Objectives
1. To understand how MRI acquisition time can be reduced with deep learning.
2. To understand the potential artefacts related to deep learning-based image reconstruction.
3. To demonstrate the applications of deep learning in the reconstruction of cardiovascular MRI data.
E³ 222-3
C. Deep learning in CT image acquisition and reconstruction
Mathias Prokop, Nijmegen / Netherlands
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.

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