Diagnostic Image Analysis Group

The Diagnostic Image Analysis Group is part of the Department of Radiology and Nuclear Medicine of Radboud University Medical Center. We develop computer algorithms to aid clinicians in the interpretation of medical images and thereby improve the diagnostic process.

The group has its roots in computer-aided detection of breast cancer in mammograms, and we have expanded to automated detection and diagnosis in breast MRI, ultrasound and tomosynthesis, chest radiographs and chest CT, prostate MRI, neuro-imaging and the analysis of retinal and digital pathology images.

It is our goal to have a significant impact on healthcare by bringing our technology to the clinic. We are therefore fully certified to develop, maintain, and distribute software for analysis of medical images in a quality controlled environment (MDD Annex II and ISO 13485). To date two products, ProCAD and CAD4TB, have been CE marked and are in active use in over ten countries.

On this site you find information about the history of the group and our collaborations, an overview of people in DIAG, current projects, publications and theses, contact information, and info for those interested to join our team.

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Jeroen van der Laak has contributed to a news article of the NOS about the success of a deep learning-based algorithm to automatically detect malignant lymph tissue in pathology slides. The algorithm, trained on data provided by the DIAG group, outperforms pathologists on this task. More info can be found on the Google research Blog and in the resulting paper.

More Research Highlights.

News

  • July 14, 2017 - Maschenka Balkenhol has won the 2017 OOR ON science award
  • June 26, 2017 - Henkjan Huisman has been appointed Associate Professor in Pelvic Imaging Biomarkers.
  • May 30, 2017 - Clarisa Sanchez has been appointed Associate Professor.
  • March 21, 2017 - Thomas van den Heuvel will present at the grande finale of Radboud Talks on the 21st of March. Tickets can be obtained here.
  • March 17, 2017 - Rashindra Manniesing received a grant from ERA-NET NEURON (940 kE) together with Anne Vik (Norway), David Menon (UK) and Paul Parizel (Belgium) to work on a new axonal injury classification system in neurotrauma imaging. In Nijmegen there will be one research position available to work on the development of deep learning algorithms.
  • March 17, 2017 - DIAG has a new vacancy for a PhD or postdoc to work on deep learning in neurotrauma imaging.
  • March 7, 2017 - The work by Midas Meijs on a new technique for visualizing vascular flow disturbances in the brain which was presented at the ECR 2017 was mentioned in Aunt Minnie .
  • March 6, 2017 - Joris Bukala started as a new PhD student at DIAG.
  • March 6, 2017 - Valentin Kotov started his master thesis research at the DIAG group.
  • March 6, 2017 - The collaborative work between DIAG and the MILD investigators on automatic detection of subsolid nodules in the MILD trial was presented at ECR 2017 and extensively covered by Auntminnie.
  • February 16, 2017 - The demonstration of the 'Multimodal Workstation for Analysis of Retinal Images' by Bart Liefers was selected as the winner of the live demonstration workshop at SPIE Medical Imaging 2017.

More News.