E³ - ECR Master Class

Clinical impact of image quantification and artificial intelligence (AI)

Lectures

1
E³ 626 - A. The role of quantification in brain imaging

E³ 626 - A. The role of quantification in brain imaging

14:29R. Buchert, Hamburg / DE

Learning Objectives
1. To learn quantification methods for brain metabolism and dementia.
2. To outline reliable quantification methods for neuroinflammation.
3. To discuss the added value of quantification.

2
E³ 626 - B. Quantitative imaging and AI in cardiovascular diseases

E³ 626 - B. Quantitative imaging and AI in cardiovascular diseases

11:45N. Prakken, Groningen / NL

Learning Objectives
1. To outline machine learning techniques and metrics for cardiac imaging.
2. To learn about quantification of cardiac and intravascular flow.
3. To understand the value of quantitative cardiac imaging for myocardial ischaemia.

3
E³ 626 - C. Quantitative imaging and radiomics in oncology

E³ 626 - C. Quantitative imaging and radiomics in oncology

13:48G. Cook, London / UK

Learning Objectives
1. To outline quantitative methods, radiomics, and machine learning in oncological molecular imaging.
2. To learn about potential targets and metrics as promising imaging biomarkers.
3. To discuss the challenges of quantitative imaging and radiomics in oncology.

E³ 626-2
15 min
A. The role of quantification in brain imaging
Ralf Buchert, Hamburg / Germany
 
1. To learn quantification methods for brain metabolism and dementia.
2. To outline reliable quantification methods for neuroinflammation.
3. To discuss the added value of quantification.
E³ 626-3
15 min
B. Quantitative imaging and AI in cardiovascular diseases
Niek Prakken, Groningen / Netherlands
 
1. To outline machine learning techniques and metrics for cardiac imaging.
2. To learn about quantification of cardiac and intravascular flow.
3. To understand the value of quantitative cardiac imaging for myocardial ischaemia.
E³ 626-4
15 min
C. Quantitative imaging and radiomics in oncology
Gary Cook, London / UK
 
1. To outline quantitative methods, radiomics, and machine learning in oncological molecular imaging.
2. To learn about potential targets and metrics as promising imaging biomarkers.
3. To discuss the challenges of quantitative imaging and radiomics in oncology.
10 min
Live Q&A: what can we quantify and what is clinically essential?