PD Dr. med Bettina Baessler

Research group leader, Consultant radiologist

University of Zurich & University Hospital Zurich

About Myself

I am a consultant radiologist with special focus on quantitative and cardiovascular imaging including radiomics at the University of Zurich and the Department of Diagnostic and Interventional Radiology of the University Hospital Zurich.

My special interest lies in the translation of quantitative imaging techniques to clinical routine and in the application of machine learning algorithms in medical imaging science. Over the past few years, my research has focused on the evaluation of the potential of radiomics and texture analysis combined with machine learning techniques for cardiac MRI. This work has led to an increasing awareness of the standardization issue in the field of radiomics. Currently, my group is working on various projects aiming to apply radiomics and deep learning to cardiac and oncological imaging, with a special focus on standardization. Since these emerging technologies require large datasets to accurately evaluate their performance, I was able to take lead in a large nationwide multicenter trial aiming at standardizing quantitative cardiac MRI.

It is my strong belief that research can only thrive through collaboration, hence my involvement in scientific societies such as the working group on cardiac imaging and of medical imaging IT of the German Radiological Society and the European Society of Medical Imaging Informatics (EuSoMII) has shown to be extremely rewarding.

No less important and rewarding for me is medical education, which has led me to develop and lead a quality improvement project for radiological teaching at my former department in Cologne, Germany. We completely overhauled teaching, providing lectures on demand and incorporating online voting systems during lectures. Since then, I have been involved in the development of the national training curriculum of medicine (Nationaler Kompetenzbasierter Lernzielkatalog Medizin, NKLM) as a speaker of the project group “digital compentencies” and as a co-speaker in the working group for the implementation of NKLM in Germany. The implementation of digital skills into the medical training curriculum is an extremely important topic, and I am excited about being part of this ongoing process.


  • Cardiovascular imaging
  • Quantitative MRI techniques
  • T1 & T2 mapping
  • Radiomics
  • Advanced statistics
  • Machine Learning
  • Artificial Intelligence


  • Habilitation (Priv.-Doz. / PD), 2018

    University of Cologne

  • Medical Doctor (M.D.), 2011

    University of Bonn

  • Medicine (Staatsexamen), 2010

    University of Bonn



Full professor of Radiology (focus on cardiovascular imaging and artificial intelligence), Head of cardiovascular imaging section

University Hospital Wurzburg

Oct 2021 – Present Wurzburg
Responsibilities include:

  • Cardiovascular imaging (clinical and research)
  • Radiomics
  • Machine Learning, AI
  • Big Data analyses

Founder and CEO of Lernrad GmbH

Lernrad GmbH

Jan 2021 – Present Germany
E-learning platform for radiology

Research group leader and Consultant radiologist

University of Zurich & University Hospital Zurich

Jul 2019 – Sep 2021 Zurich
Responsibilities include:

  • Cardiovascular MRI (clinical and research)
  • Radiomics
  • Machine Learning
  • Big Data analyses

Research group leader and Consultant radiologist

University Hospital Mannheim

Aug 2018 – Jun 2019 Mannheim
Research group Medical Imaging Informatics and Radiomics.

Research group leader and board-certified radiologist

University Hospital Cologne

Jul 2017 – Aug 2018 Cologne
Research group Multiparametric Imaging and Radiomics.

Junior research group leader and radiology resident

University Hospital Cologne

Jan 2011 – Jun 2017 Cologne
Junionr research group Multiparametric Imaging and Radiomics.


Wilhelm Conrad Roentgen award

Wachsmann innovation award 2020

For creation of ‘CoRad19’, an online education tool for radiology during the Covid pandemia

Wilhelm Friedrich award

Invest in the youth program

Best abstract award

Trainee research prize

For paper ‘Diagnostic Value of Quantitative Edema Detection Using T2-mapping in Acute Myocarditis’.

BONFOR grant for MD thesis

Fellowship by the German National Academic Foundation (Studienstiftung des Deutschen Volkes)

Upcoming Talks

Recent Publications

Quickly discover relevant content by filtering publications.

Image-Based Cardiac Diagnosis With Machine Learning - A Review

Cardiac imaging plays an important role in the diagnosis of cardiovascular disease (CVD). Until now, its role has been limited to …

Accuracy of Radiomics-Based Feature Analysis on Multiparametric Magnetic Resonance Images for Noninvasive Meningioma Grading

Peripheral Vascular Anomalies – Essentials in Periinterventional Imaging

BACKGROUND Peripheral vascular anomalies represent a rare disease with an underlying congenital mesenchymal and angiogenetic disorder. …

Machine learning in cardiovascular magnetic resonance - basic concepts and applications

Machine learning (ML) is making a dramatic impact on cardiovascular magnetic resonance (CMR) in many ways. This review seeks to …

Structured report data can be used to develop deep learning algorithms - a proof of concept in ankle radiographs

Precision, reproducibility and applicability of an undersampled multi-venc 4D flow MRI sequence for the assessment of cardiac hemodynamics

Systematic prostate biopsy still matters - A comprehensive analysis of MRI/TRUS-fusion targeted prostate biopsies across different indications

OBJECTIVES To assess if a multiparametric magnetic resonance imaging (mpMRI)-targeted biopsy (TB) strategy is precise enough to replace …

Cardiac MRI and Texture Analysis of Myocardial T1 and T2 Maps in Myocarditis with Acute versus Chronic Symptoms of Heart Failure

Background The establishment of a timely and correct diagnosis in heart failure-like myocarditis remains one of the most challenging in …

Medical students' attitude towards artificial intelligence - a multicentre survey

OBJECTIVES To assess undergraduate medical students’ attitudes towards artificial intelligence (AI) in radiology and medicine. …

Robustness and Reproducibility of Radiomics in Magnetic Resonance Imaging - A Phantom Study

OBJECTIVES The aim of this study was to investigate the robustness and reproducibility of radiomic features in different magnetic …

The role of cardiovascular magnetic resonance imaging in rheumatic heart disease

Cardiovascular involvement is a well-known feature of inflammatory rheumatic diseases, although often clinically silent, so early …

Cardiac MRI Texture Analysis of T1 and T2 Maps in Patients with Infarctlike Acute Myocarditis

Purpose To assess the diagnostic potential of texture analysis applied to T1 and T2 maps obtained with cardiac MRI for the diagnosis of …

Texture analysis and machine learning of non-contrast T1-weighted MR images in patients with hypertrophic cardiomyopathy-Preliminary results

PURPOSE To test in a first proof-of-concept study whether texture analysis (TA) allows for the detection of myocardial tissue …

Subacute and Chronic Left Ventricular Myocardial Scar - Accuracy of Texture Analysis on Nonenhanced Cine MR Images

Purpose To test whether texture analysis (TA) allows for the diagnosis of subacute and chronic myocardial infarction (MI) on …

Teaching Activities

Go for IT webinar series

A webinar series to teach basics statistics, machine learning and R programming from radiologists for radiologists. Hosted by the …

Radio-RESET e-learning videos on YouTube

E-learning videos for the technical basics of the main modalities in radiology - X-ray, computed tomography, and magnetic resonance …