Deep learning and image quality - ESR Connect

Special Focus Session - Organised by ESR eHealth and Informatics Subcommittee

SF 18 - Deep learning and image quality

  • 3 Lectures
  • 56 Minutes
  • 3 Speakers

Lectures

1
SF 18 - AI-enhanced image processing: noise reduction

SF 18 - AI-enhanced image processing: noise reduction

18:30J. Greffier, Nimes / France

Learning Objectives
1. To gain basic understanding of noise and how to measure it in radiologic imaging.
2. To learn the principles of AI-enhanced noise reduction in medical imaging.
3. To know the advantages and inconveniences of AI-enhanced noise reduction.

2
SF 18 - How to use deep learning to improve image quality

SF 18 - How to use deep learning to improve image quality

17:56Y. Nakamura, Hiroshima / Japan

Learning Objectives
1. To understand how image quality in radiology is traditionally improved.
2. To learn how deep learning can be used to improve image quality.
3. To explain the advantage of using deep learning to improve image quality.

3
SF 18 - AI helping to optimise dose and contrast agent application

SF 18 - AI helping to optimise dose and contrast agent application

20:11C. Hoeschen, Magdeburg / Germany

Learning Objectives
1. To learn about the relationship between radiation dose, contrast medium application and image quality.
2. To understand how AI can be used to optimise dose and contrast medium application.

Speakers

Presenter

Joel Greffier

Nimes, France

Presenter

Yuko Nakamura

Hiroshima, Japan

Presenter

Christoph Hoeschen

Magdeburg, Germany

This course is only accessible for persons who have subscribed to the ESR Premium Education Package.