Dr Mariusz Bajger

Mariusz Bajger
Position/s:Lecturer
School of Computer Science, Engineering and Mathematics
Phone: +61 8 82013984
Email:
Location: Information, Science & Technology (226)
Postal address: GPO Box 2100, Adelaide 5001, South Australia

Biography

Mariusz Bajger received the M.Sc. in Applied Mathematics degree from the Jagiellonian University in Cracow (Poland) in 1988 and the PhD degree in mathematics from the University of Queensland in 1996. Since 2002 he is a full-time lecturer with the School of Computer Science, Engineering and Mathematics at the Flinders University. His research interests include applications of mathematics and computer science to problems in medical image analysis and pattern recognition with focus on breast cancer detection in screening mammograms, whole-body CT segmentation and computational human anatomy,

Qualifications

PhD Mathematics, University of Queensland, Australia, 1996.
MSc Applied Mathematics, Jagiellonian University, Poland, 1988.

Honours, awards and grants

  • Channel 7 Children's Research Foundation Grant, 2012-2013
  • Lyn Wrigley Breast Cancer Research & Development Fund, Breast Cancer Research Grant, 2011
  • Lyn Wrigley Breast Cancer Research & Development Fund, Breast Cancer Research Grant, 2010
  • Lyn Wrigley Breast Cancer Research & Development Fund, Breast Cancer Research Grant, 2009
  • National Breast Cancer Foundation Grant 2006-2008
  • Lyn Wrigley Breast Cancer Research & Development Fund, Breast Cancer Research Grant, 2007
  • 3rd prize in M. Kuczma's competition for the best paper in Functional Equations written by Polish author in 2004.

Key responsibilities

Director of Postgraduate Coursework Studies (Information Technology and Software Engineering)

  • Computer Science/Information Technology Honours
  • Master of Information Technology
  • Master of Science (Computer Science)
  • Graduate Diploma in Information Technology
  • Graduate Certificate in Information Technology

Teaching

Topic Coordinator:

Research and supervision

Research expertise

  • Artificial intelligence and image processing

Research interests

Medical Image Analysis, in particular mammography and computational anatomy.

Supervisory interests

  • Medical image analysis

RHD research supervision

Current

Associate supervisor: Medical Image Analysis (1);

Completion

Associate supervisor: Medical Image Analysis (1); Mathematical Modeling (1);

Publications

Book chapters
Omondi, A.R., Rajapakse, J.C. and Bajger, M. (2006). FPGA Neurocomputers. In Amos Omondi, Jagath Rajapakse, ed. FPGA Implementations of Neural Networks. Dordrecht, The Netherlands: Springer, pp. 1-36.
Refereed journal articles
Bajger, M., Lee, G.N. and Caon, M. (2013). 3D segmentation for multi-organs in CT images. Electronic Letters on Computer Vision and Image Analysis, 12(2), pp.13-27. [online]. Available from: http://elcvia.cvc.uab.es/.
Bajger, M. and Omondi, A. (2008). Low-error, high-speed approximation of the sigmoid function for large FPGA Implementations. Journal of Signal Processing Systems, 52(2), pp.137-151. [online]. Available from: http://dx.doi.org/10.1007/s11265-007-0140-z.
Ma, F., Bajger, M., Slavotinek, J.P. and Bottema, M.J. (2007). Two graph theory based methods for identifying the pectoral muscle in mammograms. Pattern Recognition, 40(9), pp.2592-2602. [online]. Available from: http://dx.doi.org/10.1016/j.patcog.2006.12.011.
Bajger, M. (2004). On the composite Pexider equation modulo a subgroup. Publicationes Mathematicae-Debrecen, 64(1-2), pp.39-61.
Refereed conference papers
Lee, G., Bajger, M. and Caon, M. (2012). Multi-organ segmentation of CT images using statistical region merging. In C. Hellmich, M. H. Hamza, D. Simsik, ed. Proceedings of the Ninth IASTED International Conference on Biomedical Engineering. Ninth IASTED International Conference on Biomedical Engineering, BioMed 2012. pp. 199-206. [online]. Available from: http://dx.doi.org/10.2316/P.2012.764-052.
Bottema, M., Bajger, M., Williams, S. and Ma, F. (2012). MATHEMATICS IN MEDICAL IMAGE ANALYSIS: A FOCUS ON MAMMOGRAPHY. In Proceedings of the 6th SEAMS-GMU International Conference on Mathematics and Its Applications. MATHEMATICS AND ITS APPLICATIONS IN THE DEVELOPMENT OF SCIENCES AND TECHNOLOG. pp. 51-64.
Bajger, M., Lee, G. and Caon, M. (2012). Full-body CT segmentation using 3D extension of two graph-based methods: a feasibility study. In M Petrou, AD Sappa & GA Triantafyllids, ed. Proceedings of the Ninth IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2012). Signal Processing, Pattern Recognition and Applications (SPPRA 2012). pp. 43-50. [online]. Available from: http://dx.doi.org/10.2316/P.2012.778-050.
Ma, F., Bajger, M., Williams, S. and Bottema, M.J. (2010). Improved detection of cancer in screening mammograms by temporal comparison. In Joan Marti, Arnau Oliver, Jordi Freixenet, Robert Marti, ed. Lecture Notes in Computer Science: Digital Mammography IWDM 2010. International Workshop on Digital Mammography. pp. 752-759.
Bajger, M., Ma, F., Williams, S. and Bottema, M.J. (2010). Mammographic mass detection with statistical region merging. In Proceedings: DICTA 2010. Digital Image Computing: Techniques and Applications. pp. 27-32.

Show all publications

Book chapters
Omondi, A.R., Rajapakse, J.C. and Bajger, M. (2006). FPGA Neurocomputers. In Amos Omondi, Jagath Rajapakse, ed. FPGA Implementations of Neural Networks. Dordrecht, The Netherlands: Springer, pp. 1-36.
Refereed journal articles
Bajger, M., Lee, G.N. and Caon, M. (2013). 3D segmentation for multi-organs in CT images. Electronic Letters on Computer Vision and Image Analysis, 12(2), pp.13-27. [online]. Available from: http://elcvia.cvc.uab.es/.
Bajger, M. and Omondi, A. (2008). Low-error, high-speed approximation of the sigmoid function for large FPGA Implementations. Journal of Signal Processing Systems, 52(2), pp.137-151. [online]. Available from: http://dx.doi.org/10.1007/s11265-007-0140-z.
Ma, F., Bajger, M., Slavotinek, J.P. and Bottema, M.J. (2007). Two graph theory based methods for identifying the pectoral muscle in mammograms. Pattern Recognition, 40(9), pp.2592-2602. [online]. Available from: http://dx.doi.org/10.1016/j.patcog.2006.12.011.
Bajger, M. (2004). On the composite Pexider equation modulo a subgroup. Publicationes Mathematicae-Debrecen, 64(1-2), pp.39-61.
Refereed conference papers
Bottema, M., Bajger, M., Williams, S. and Ma, F. (2012). MATHEMATICS IN MEDICAL IMAGE ANALYSIS: A FOCUS ON MAMMOGRAPHY. In Proceedings of the 6th SEAMS-GMU International Conference on Mathematics and Its Applications. MATHEMATICS AND ITS APPLICATIONS IN THE DEVELOPMENT OF SCIENCES AND TECHNOLOG. pp. 51-64.
Bajger, M., Lee, G. and Caon, M. (2012). Full-body CT segmentation using 3D extension of two graph-based methods: a feasibility study. In M Petrou, AD Sappa & GA Triantafyllids, ed. Proceedings of the Ninth IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2012). Signal Processing, Pattern Recognition and Applications (SPPRA 2012). pp. 43-50. [online]. Available from: http://dx.doi.org/10.2316/P.2012.778-050.
Lee, G., Bajger, M. and Caon, M. (2012). Multi-organ segmentation of CT images using statistical region merging. In C. Hellmich, M. H. Hamza, D. Simsik, ed. Proceedings of the Ninth IASTED International Conference on Biomedical Engineering. Ninth IASTED International Conference on Biomedical Engineering, BioMed 2012. pp. 199-206. [online]. Available from: http://dx.doi.org/10.2316/P.2012.764-052.
Ma, F., Bajger, M., Williams, S. and Bottema, M.J. (2010). Improved detection of cancer in screening mammograms by temporal comparison. In Joan Marti, Arnau Oliver, Jordi Freixenet, Robert Marti, ed. Lecture Notes in Computer Science: Digital Mammography IWDM 2010. International Workshop on Digital Mammography. pp. 752-759.
Bajger, M., Ma, F., Williams, S. and Bottema, M.J. (2010). Mammographic mass detection with statistical region merging. In Proceedings: DICTA 2010. Digital Image Computing: Techniques and Applications. pp. 27-32.
Bajger, M., Ma, F. and Bottema, M.J. (2009). Automatic tuning of MST segmentation of mammograms for registration and mass detection algorithms. In Shi, Zhang, Bottema, Lovell, Meader, ed. DICTA 2009 Digital Image Computing Techniques and Applications. Digital Image Computing Techniques and Applications. pp. 400-407.
Ma, F., Bajger, M. and Bottema, M.J. (2009). Automatic mass segmentation based on adaptive pyramid and sublevel set analysis. In Shi, Zhang, Bottema, Lovell, Meader, ed. DICTA 2009 Digital Image Computing Techniques and Applications. Digital Image Computing Techniques and Applications. pp. 236-241.
Ma, F., Bajger, M. and Bottema, M.J. (2008). Temporal analysis of mammograms based on graph matching. In Krupinski, Elizabeth, ed. Digital Mammography (Lecture Notes in Computer Science series). 9th International Workshop on Digital Mammography. pp. 158-165.
Susukida, H., Ma, F. and Bajger, M. (2008). Automatic tuning of a graph-based image segmentation method for digital mammography applications. In 2008 5th IEEE international symposium on biomedical imaging: From nano to macro. 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI08). pp. 89-92.
Ma, F., Bajger, M. and Bottema, M.J. (2007). Robustness of two methods for segmenting salient features in screening mammograms. In Proceedings of DICTA. 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA). pp. 112-117.
Ma, F., Bajger, M., Slavotinek, J.P. and Bottema, M.J. (2006). Validation of Graph Theoretic Segmentation of the Pectoral Muscle. In Astley, S. (Sue), ed. Digital Mammography - 8th International Workshop, IWDM 2006. 8th International Workshop, IWDM 2006. pp. 642-649.
Bajger, M. and Omondi, A.R. (2006). Implementation of square-root and exponential functions for large FPGAs. In Chris Jesshope and Colin Egan, ed. Lecture Notes in Computer Science. 11th Asia-Pacific Conference, ACSAC 2006. pp. 6-23.
Bajger, M., Ma, F. and Bottema, M.J. (2005). Minimum spanning trees and active contours for identification of the pectoral muscle in screening mamograms. In BC Lovell, AJ Maeder, T Caelli, S Ourselin, ed. Proceedings Digital Image Computing: Techniques and Applications DICTA 2005. Digital Image Computing Techniques and Applications 2005. p. 47.
Ma, F., Bajger, M. and Bottema, M.J. (2005). Extracting the pectoral muscle in screening mammograms using a graph pyramid. In Brian C Lovell and Anthony J Maeder, ed. Proceedings of the APRS Workshop on Digital Image Computing (WDIC) 2005. APRS Workshop on Digital Image Computing.
Conference publications
Sidik, W., Bottema, M. and Bajger, M. (2011). A Cross-Species Avian-Human Influenza Epidemic Model: Transport related co-infection. In Proceedings of 7th ICIAM Conference. 7th ICIAM Conference 2011.
Sidik, W., Bottema, M. and Bajger, M. (2011). A Cross-Species Avian-Human Influenza Epidemic Model: Effects of human behaviours on the disease spread and control. In Proceedings of the 6th SEAMS-GMU International Conference on Mathematics and Applications. 6th SEAMS-GMU Conference.
Sidik, W., Bottema, M. and Bajger, M. (2011). A Cross-Species Avian Human Influenza Epidemic Model: Effects of some control strategies. In Proceedings of ANZIAM Conference. ANZIAM Conference 2011.
Lee, G., Bajger, M. and Caon, M. (2011). CAnat: An Algorithm for the Automatic Segmentation of Anatomy of Medical Images. In EPSM-ABEC 2011 Conference. Australasian Physical & Engineering Sciences in Medicine (APESM-ABEC) 2011.
Bottema, M., Bajger, M., ma, F. and Williams, S. (2011). Mathematics in medical image analysis: a focus on mammography. In Proceedings of the 6th SEAMS-GMU International Conference on Mathematics and Applications. 6th SEAMS-GMU Conference.
Sidik, W., Bottema, M. and Bajger, M. (2011). A Cross-Species Avian-Human Influenza Epidemic Model: Economic trade off on the disease spread and controls. In Proceedings of AICST Conference. ACIKITA International Conference of Science and Technology.
Sidik, W., Bottema, M. and Bajger, M. (2010). A Cross-Species Avian Human Influenza Epidemic Model: Disease Spread. In Proceedings of 54th Australian Mathematical Society Conference. 54th AustMS Conference.
Ma, F., Bajger, M. and Bottema, M.J. (2008). A graph matching based automatic regional registration method for sequential mammogram analysis. In Geiger, M. L. and Karssemeijer, ed. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Medical Imaging 2008: Computer-Aided Diagnosis.
Goel, N., Bajger, M. and Tomczak, M. (2007). Civilizations of the world, a new electronic time atlas concept. In L. Gomez Chova, D. Marti Belenguer and I. Candel Torres, ed. INTED2007 Proceedings. INTED2007: International Technology, Education and Development Conference.

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Professional and community engagement

Professional memberships

  • Australian Pattern Recognition Society (APRS)
  • Association for Computing Machinery (ACM)
Journal reviewer
  • Australasian Physical and Engineering Sciences in Medicine
  • Computer Methods and Programs in Biomedicine
  • IEEE Transactions on Biomedical Engineering
  • International Journal of Computer Systems Science & Engineering
  • IEEE Transactions on Very Large Scale Integration Systems

Expertise for media contact

  • Image Analysis
  • Computer Aided Screening Mammography

Further information

Documents



inspiring achievement