Diagnostic Image Analysis Group
The Diagnostic Image Analysis Group is part of the Department of Radiology of Radboud University Nijmegen Medical Centre. 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 computer-aided detection and computer-aided diagnosis in breast MRI, ultrasound and tomosynthesis, chest radiographs, chest CT, prostate MRI, neuro-imaging and retinal images.
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.
The human lungs consist of five parts, the lobes (the right lung has three lobes, the left lung two). Segmenting these lobes in CT scans of the lungs is not a simple task. Bianca Lassen developed an automatic method to precisely delineate the lobes. She evaluated the method on 55 scans for a publicly available data set LOLA11. The renderings above illustrate the results on eight of these scans. More...
For more research highlights, see the Research Highlights Archive.
- May 12, 2013: Positions for PhD students and post-doctoral researchers in automating CT lung screening are available.
- March 29, 2013: The EU FP7 ASSURE project's website is online at www.assure-project.eu.
- March 10, 2013: Colin Jacobs presented a method to automatically classify pulmonary nodules as solid, part-solid, or non-solid at the European Congress of Radiology in Vienna. His work was extensively covered by Aunt Minnie.
- March 5, 2013: The work of Jaime Melendez on stand-alone mammography CAD was covered by Aunt Minnie.
- February 1, 2013: Bram van Ginneken was awarded a VICI grant, in the NWO Vernieuwingsimpuls programme, for his proposal Lung CT Screening: More for Less.
For older news, see the News Archive.