1st Virtual Training School “Radiomics and AI for Molecular Medicine”

From August-31 to September-2, 2020

1st Virtual Training School “Radiomics and AI for Molecular Medicine”

From August-31 to September-2, 2020

The first Summer School on “Radiomics and AI for Molecular Medicine” will be held from August 31 to September 2, 2020. The school will be entirely virtual. It will provide training in the basic concepts of Radiomcis and AI for translation in to nuclear and molecular medicine applications. Trainees will be encouraged to bring data and to share challenges from their local sites. During the course, trainees will be working with the OpenSource platform LifeX so as to gain hands-on experience with feature extraction and, subsequently, machine-learning and prediction models. The faculty is composed of international experts in the fields of nuclear medicine imaging, computer sciences and AI. The summer school is limited to 40 participants. Training fees are 50 EUR for academic delegates and 120 EUR for delegates from industry.

München Großhadern

Target audience

Nuclear medicine specialists. Medical Physicists. Computer scientists and IT experts. Clinical researchers. All with a background in nuclear medicine and basic image processing.

München OPZ

Key objectives

To understand image- and quantification-based biomarkers in nuclear medicine and ancillary domains. To appreciate the need for high quality inpout data to AI. To comprehend the basic concepts of AI, machine learning and features. To get acquainted with LifeX (as one option for OpenSource feaure exteraction). To learn to build on-demand prediction models. To appreciate the need for assessing accuracu and reproducibility of prediction models.


This online course is composed of multiple in-depth lectures an interactive sessions using LifeX

  • The role of Radiomics and AI in clinical applications
  • Planning clinical research activities in the world of AI
  • Current affairs of AI in clinical scenarios
  • Data preparation and accounting for data imbalances
  • Feature extraction and variations
  • Data analysis and the curse of dimensionality
  • Model interpretaion and validation


Our faculty comes with in-depth experience and expertise in image data generation and processing with a focus on molecular imaging and machine learning. Together they provide a unique teaching experience for users and aspiring talents in the domain of AI-based decision support systems.

Time table


Time Monday, Aug 31 Tuesday, Sep 1 Wednesday, Sep 2
09.00 Course Introduction
(Papp, Ziegler, Buvat)
Feedback Day 1
Feedback Day 2
09.30 Round of Introduction
(40 participants : Academia 50 EUR, Industry 120 EUR)
Research Planning for AI-projects
(I Buvat)
Building Models
(L Papp)
10:15 Break Q&A Q&A
10:30 A clinical perspective on Radiomics and AI
(M Hacker)
Data preparation
(L Papp)
Validation and model interpretation
(L Kaiser)
11:30 Roundtable
(MD and Tech geeks)
(AI experts)
(AI experts)
11:45 Break Break Break
12:00 Harmonized NM imaging
(T Beyer)
Feature extraction
(F Orlhac)
A pathologist’s perspective on Radiomics and AI
(K Steiger)
12:45 Roundtable
(MD and Tech geeks)
(AI experts)
13:00 Break Break Break
14:00 Meet the LIFExpert Meet the LIFExpert Meet the LIFExpert
15:00 End-of-day End-of-day End-of-day and Farewell

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