Artificial Intelligence in Neuroradiology

Principle Investigator

Senior Advisors

Univ.-Prof. Dr. Jan Borggrefe, MD (Johannes Wesling Klinikum Minden - University Hospitals of the Ruhr-University Bochum)

Michael Perkuhn, MD (Philips GmbH Innovative Technologies)

Research Topics


Our AI research group aims to develop novel methods to improve brain imaging and establish new approaches for non-invasive tumor characterization. Recent advances in processing of imaging data with use of Artificial Intelligence and introduction of quantitative MR imaging sequences provide numerous opportunities for clinicians to improve patient management and therapy planning.

One of our main interests is to automatize brain tumor detection and consecutive segmentation using Deep Learning based techniques to free up radiologists’ resources and enhance reproducibility of imaging data. In combination with newly developed imaging sequences such as MR Fingerprinting, we want to determine tumor biology, non-invasively. Finally, we use Artificial Intelligence for studies regarding non-invasive multiparametric diagnostics and studies evaluating multimodal tumor therapy.

Neurovascular Imaging

Another focus of our research group is the automated detection of neurovascular pathologies with special interest in intracranial aneurysms. Further, we want to use automatically generated segmentations to stratify patient risk and facilitate endovascular or surgical treatment.

Grant support

  • Faculty of Medicine and University Hospital Cologne


  • Institute for Diagnostic Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling Klinikum Minden, University Hospitals of the Ruhr-University Bochum, Germany
  • Department of Neurosurgery and Stereotaxy, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  • Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Germany
  • Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
  • Philips GmbH Innovative Technologies, Aachen, Germany
  • Lung Cancer Group, Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
Selected Publications

  • Contrast-Enhanced Black Blood MRI Sequence Is Superior to Conventional T1 Sequence in Automated Detection of Brain Metastases by Convolutional Neural Networks. Diagnostics 2021
  • Fully Automated MR Detection and Segmentation of Brain Metastases in Non-small Cell Lung Cancer Using Deep Learning. J Magn Reson Imaging. 2021
  • Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage. Neuroradiology 2021
  • Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model. Am J Neuroradiol. 2021
  • Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning. Sci Rep. 2020
  • Primary Central Nervous System Lymphoma: Clinical Evaluation of Automated Segmentation on Multiparametric MRI Using Deep Learning. J Magn Reson Imaging. 2020
  • Automated Meningioma Segmentation in Multiparametric MRI: Comparable Effectiveness of a Deep Learning Model and Manual Segmentation. Clin Neuroradiol. 2020
  • Accuracy of Radiomics-Based Feature Analysis on Multiparametric Magnetic Resonance Images for Noninvasive Meningioma Grading. World Neurosurg. 2019
  • Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI. Eur Radiol. 2019
  • Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine. Invest Radiol. 2018

Group members

Dr. Liliana Caldeira, PhD
Dr. Carsten Gietzen, MD
Dr. Lukas Goertz, MD
Dr. Jan-Peter Grunz, MD
Dr. Cornelia Hoyer, MD
Dr. Stephanie Jünger, MD
PD Dr. Christoph Kabbasch, MD
Mr. Jonathan Kottlors, MD
Dr. Simon Lennartz, MD
Mr. Michael Perkuhn, MD
Dr. Rahil Shahzad, PhD
Dr. Marco Timmer, MD
Mr. Frank Thiele, MSc
Dr. Niklas von Spreckelsen, MD
Dr. David Zopfs, MD

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