Bram van Ginneken, University Medical Center Utrecht
This tutorial will explain feature extraction and classification techniques that form the basics of computer-aided detection and computer-aided diagnosis systems. This is one of the most rapidly expanding areas in medical image analysis. Well-known application areas are mammography, chest imaging and virtual colonoscopy and many other applications are emerging. Despite the large differences in image data, these systems employ a common set of techniques from image processing and pattern recognition and machine learning. These techniques are the topic of the tutorial and are illustrated with a large number of recent practical applications.
Bram van Ginneken studied Physics at the Eindhoven University of Technology and at Utrecht University. In March 2001, he obtained his Ph.D. at the Image Sciences Institute on Computer-Aided Diagnosis in Chest Radiography. Ever since, he has been leading the Computer-Aided Diagnosis group at the Image Sciences Institute. He has (co-)authored over 30 journal publications. He is Associate Editor of IEEE Transactions on Medical Imaging and member of the program committee of the Image Processing and the Computer-Aided Diagnosis conferences of SPIE Medical Imaging.