Jeroen Eggermont

Introduction

Jeroen Eggermont is a scientific researcher in the section ‘vascular & molecular imaging’ in the division of image processing. He received his M.Sc. degree in computer science at Leiden University in 1998 with a thesis entitled “Rule-extraction and learning in the BP-SOM architecture”.

In 2005 he received his Ph.D. from Leiden University with a thesis entitled “Data Mining using Genetic Programming: Classification and Symbolic Regression”. Later that year he started as a post-doctoral researcher at the division of image processing of the Leiden Univeristy Medical Center on the NWO-Savage (Self-Adaptive Vision Agents using Genetic Evolution) project. Currently his work in mainly focussed on automatic analysis of Intravascular Ultrasound and Optical Coherence Tomography images.

Area(s) of expertise

• Intravascular Ultrasound (IVUS)
• Optical Coherence Tomography (OCT)
• Atherosclerotic Plaque Characterization
• Natural Computing
• Optimization
• Data Mining

Publications

• Metamodel-Assisted Mixed Integer Evolution Strategies and Their Application to Intravascular Ultrasound Image Analysis Rui Li, Micahel T.M. Emmerich, Jeroen Eggermont, Ernst G.P. Bovenkamp, Thomas Bäck, Jouke Dijkstra and Johan H.C. Reiber Proceedings of the 2008 Congress of Evolutionary Computation (CEC’08), 2008
• Optimizing Computed Tomographic Angiography Image Analysis using Fitness Based Partitioning (Best Paper Award) Jeroen Eggermont, Rui Li, Ernst Bovenkamp, Henk Marquering, Michael Emmerich, Aad van der Lugt, Thomas Bäck, Jouke Dijkstra and Johan H.C. Reiber Applications of Evolutionary Computing: Evoworkshops 2008 (EvoIASP 10) Proceedings, LNCS, 2008
• Towards Dynamic Fitness Based Partitioning for Intravascular UltraSound Image Anayalys (extended abstract) Rui Li, Jeroen Eggermont, Michael T.M.Emmerich, Ernst G.P. Bovenkamp, Thomas Bäck, Jouke Dijkstra and Johan H.C. Reiber Proceedings of the 19th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC’07), 2007
• Strategies for Affect-Controlled Action-Selection in Soar-RL Eric Hogewoning, Joost Broekens, Jeroen Eggermont and Ernst G.P. Bovenkamp Proceedings of the 2nd work-conference on the Interplay between Natural and Artificial Computation Part 2 (IWINAC’07), LNCS 4528, 2007
• Towards Dynamic Fitness Based Partitioning for Intravascular UltraSound Image Analysis Rui Li, Michael T.M. Emmerich, Jeroen Eggermont, Ernst G.P. Bovenkamp, Thomas Bäck, Jouke Dijkstra and Johan H.C. Reiber Applications of Evolutionary Computing: Evoworkshops 2007 (EvoIASP) Proceedings, LNCS 4448, 2007
• Extending NK Landscapes to the Mixed-Integer Domain (extended abstract) Jeroen Eggermont, Ernst Bovenkamp, Rui Li, Michael Emmerich Thomas Bäck, Jouke Dijkstra and Hans Reiber Proceedings of the 18th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC’06), 2006
• Optimizing Parameters of Coronary Vessel Image Analysis Using Evolution Strategies (extended abstract) Michael Emmerich, Rui Li, Jeroen Eggermont, Ernst Bovenkamp, Thomas Bäck, Jouke Dijkstra and Hans Reiber Proceedings of the 18th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC’06), 2006
• Optimzing IVUS Lumen Segementations using Evolutionary Algorithms Ernst G.P. Bovenkamp, Jeroen Eggermont, Rui Li, Michael T.M. Emmerich, Thomas Bäck, Jouke Dijkstra and Johan H.C. Reiber Proceedings of the 1st International Workshop on Computer Vision for Intravascular and Intracardiac Imaging, MICCAI 2006
• Mixed-Integer NK Landscapes Rui Li, Michael T.M. Emmerich, Jeroen Eggermont, Ernst G.P. Bovenkamp, Thomas Bäck, Jouke Dijkstra and Johan H.C. Reiber Proceedings of the 9th International Conference on Parallel Problem Solving from Nature (PPSN IX), LNCS 4193, 2006
• Mixed-Integer Optimization of Coronary Vessel Image Analysis using Evolution Strategies Rui Li, Michael T.M. Emmerich, Jeroen Eggermont, Ernst G.P. Bovenkamp, Thomas Bäck, Jouke Dijkstra and Johan H.C. Reiber Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2006
• Optimizing Parameters of Intravascular Ultrasound Image Analysis Systems using Mixed-Integer Evolution Strategies Rui Li, Michael T.M. Emmerich, Thomas Bäck, Ernst G.P. Bovenkamp, Jeroen Eggermont, Jouke Dijkstra and Johan H.C. Reiber Poster Proceedings Adaptive Computing in Design and Manufacture (ACDM) 2006
• Mixed-Integer Evolution Strategies and Their Application to Intravascular Ultrasound Image Analysis (Best Paper Award nomination) Rui Li, Michael T.M. Emmerich, Ernst G.P. Bovenkamp, Jeroen Eggermont, Thomas Bäck, Jouke Dijkstra and Johan H.C. Reiber Applications of Evolutionary Computing: Evoworkshops 2006 (EvoIASP) Proceedings, LNCS 3907, 2006
• Data Mining using Genetic Programming: Classification and Symbolic Regression J. Eggermont PhD Thesis (2005)
• Detecting and Pruning Introns for Faster Decision Tree Evolution J. Eggermont, J.N. Kok and W.A. Kosters Proceedings of the 8th International Conference on Parallel Problem Solving From Nature (PPSN VIII), LNCS 3242 , 2004
• Genetic Programming for Data Classification:Partitioning the Search Space J. Eggermont, J.N. Kok and W.A. Kosters Proceedings of the 19th Annual ACM Symposium on Applied Computing (SAC’04), 2004
• Genetic Programming for Data Classification:Refining the Search Space J. Eggermont, J.N. Kok and W.A. Kosters Proceedings of the 15th Belgium Netherlands Artificial Intelligence Conference (BNAIC’03), 2003
• Evolving Fuzzy Decision Trees for Data Classification (extended abstract) J. Eggermont Proceedings of the 14th Belgium Netherlands Artificial Intelligence Conference (BNAIC’02), 2002
• Dynamic Optimization using Evolutionary Algorithms with a Case-based Memory J. Eggermont and T. Lenaerts Proceedings of the 14th Belgium Netherlands Artificial Intelligence Conference (BNAIC’02), 2002
• Evolving Fuzzy Decision Trees with Genetic Programming and Clustering J. Eggermont Proceedings of the Fifth European Conference on Genetic Programming (EuroGP’02), LNCS 2278 , 2002
• Knowledge discovery and evolutionary computation – a partial abstract of my Ph.D J. Eggermont Proceedings of the Brussels Evolutionary Algorithms Day (BEAD-2001)
• Non-stationary Function Optimization using Evolutionary Algorithms with a Case-based Memory J. Eggermont and T. Lenaerts Technical Report TR 2001-11, 2001
• Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems J. Eggermont and J.I. van Hemert Proceedings of the Fourth European Conference on Genetic Programming (EuroGP’01) LNCS 2038 , 2001
• Raising the Dead; Extending Evolutionary Algorithms with a Case-Based Memory J. Eggermont, T. Lenaerts, S. Poyhonen and A. Termier Proceedings of the Fourth European Conference on Genetic Programming (EuroGP’01) LNCS 2038 , 2001
• Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming J. Eggermont and J.I. van Hemert. Proceedings of the Twelveth Belgium Netherlands Conference on Artificial Intelligence (BNAIC’00), 2000.
• Comparing genetic programming variants for data classification (extended abstract) J. Eggermont, A.E. Eiben, and J.I. van Hemert. Proceedings of the Eleventh Belgium Netherlands Conference on Artificial Intelligence (BNAIC’99), 1999.
• A comparison of genetic programming variants for data classification J. Eggermont, A.E. Eiben, and J.I. van Hemert. Proceedings of the Third Symposium on Intelligent Data Analysis (IDA-99), LNCS 1642 , 1999.
• Adapting the fitness function in GP for data mining J. Eggermont, A.E. Eiben, and J.I. van Hemert. Proceedings of Second European Workshop on Genetic Programming (EuroGP’99), LNCS 1598 , 1999.
• Rule-extraction and learning in the BP-SOM architecture J. Eggermont. Internal Report IR-98-16, Leiden University, 1998 (Master Thesis).

Contact

Section Vascular and Molecular Imaging
Division of Image Processing (LKEB)
Department of Radiology
Leiden University Medical Center

PO Box 9600
2300 RC
Leiden, The Netherlands

E-mail: J.Eggermont@lumc.nl