Lecturer

Computer Sc, Engineering & Mathematics

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 1999 he is a lecturer in Computer Science 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 digital pathology image analysis.

PhD Mathematics, University of Queensland, Australia, 1996.

MSc Applied Mathematics, Jagiellonian University, Poland, 1988.

- Faculty of Science and Engineering Reinventing Teaching and Learning Grant, 2016
- 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.

- Deputy Director of Study (Mathematics)

- COMP1102 Computer Programming 1
- COMP2781 Computer Mathematics
- COMP7702 Pattern Recognition
- COMP8102 Computer Programming 1 GE
- COMP8781 Computer Mathematics GE
- ENGR1721 Engineering Programming
- ENGR8800 Engineering Programming GE
- MATH1122 Mathematics 1B

Medical Image Analysis, mammography, image processing, image segmentation, pattern recognition.

- Medical image analysis
- Pattern recognition

Principal supervisor
: Image Analysis
(1)
;

Associate supervisor
: Mammography
(1)
;

Associate supervisor
: Mathematical Modeling
(1)
; Medical Image Analysis
(2)
;

- Book chapters
- Conference publications
- Refereed conference papers
- Refereed journal articles
- Selected publications

- 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.

[10.1007/0-387-28487-7_1] [Scopus]

- Lee, G.N., Bajger, M., Caon, M., Bibbo, G. and Ng, M. (2016). Superpixels for the Visible Human Project and human anatomical voxel model construction. In Computer Assisted Radiology and Surgery: Proceedings of the 30th International Congress and Exhibition. Springer. CARS 2016 – Computer Assisted Radiology and Surgery. Heidelberg, Germany. Jun 2016, pp. 219-220.

[10.1007/s11548-016-1412-5] - Lee, G. and Bajger, M. (2014). Application of statistical inference in medical images. In Proceedings of ANZIAM 2014. ANZIAM 2014 Conference. Rotorua, New zealand. Feb 2014.
- Lee, G., Bajger, M. and Caon, M. (2014). FBIseg tool for the visible human project. In CARS 2014 Proceeding of the 28th International Congress and Exhibition in International Journal of Computer Assisted Radiology and Surgery. Springer. 28th International Congress and Exhibition on Computer Assisted Radiology and Surgery. Fukuoka, Japan. Jun 2014, pp. 40-41.
- Lee, G. and Bajger, M. (2013). Statistical inference and medical image segmentation. In Proceedings of the 49th ANZIAM Conference. ANZIAM Conference 2013.
- 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. Darwin. Aug 2011.
- Sidik, W.A., 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. Adelaide. Jan 2011.
- Sidik, W.A., 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. Jakarta, Indonesia. Jul 2011.
- Sidik, W.A., Bottema, M. and Bajger, M. (2011). A Cross-Species Avian-Human Influenza Epidemic Model: Transport related co-infection. In Proceedings of 7th ICIAM Conference. Canada7th ICIAM Conference 2011. Vancouver, Canada. Jul 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.A., 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. Jogjakarta. Jul 2011.
- Sidik, W.A., Bottema, M. and Bajger, M. (2010). A Cross-Species Avian Human Influenza Epidemic Model: Disease Spread. In Proceedings of 54th Australian Mathematical Society Conference. Brisbane, Australia54th AustMS Conference. Brisbane. Sep 2010.
- 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. SPIE. Medical Imaging 2008: Computer-Aided Diagnosis. San Diego, USA. Feb 2008.

[10.1117/12.770322] [Scopus] - 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. Valencia, SpainINTED2007: International Technology, Education and Development Conference. Valencia, Spain. Mar 2007.

- Saha, R., Bajger, M. and Lee, G.N. (2016). Spatial Shape Constrained Fuzzy C-Means (FCM) Clustering for Nucleus Segmentation in Pap Smear Images. In Alan Wee-Chung Liew, Brian Lovell, Clinton Fookes, Jun Zhou, Yongsheng Gao, Michael Blumenstein, and Zhiyong Wang, ed. DICTA 2016. IEEE. 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Gold Coast, Australia. Nov 2016, pp. 320-327.
- Sajeev, S., Bajger, M. and Lee, G.N. (2016). Improving Breast Mass Segmentation in Local Dense Background: an Entropy based Optimization of Statistical Region Merging Method. In Breast Imaging: 13th International Workshop, IWDM 2016, LNCS 9699. Springer International Publishing. Breast Imaging: 13th International Workshop, IWDM 2016. Malmo, Sweden. Jun 2016, pp. 635-644.

[10.1007/978-3-319-41546-8] - Sedlar, J., Bajger, M., Caon, M. and Lee, G.N. (2016). Model-guided segmentation of liver in CT and PET-CT images of child patients based on statistical region merging. In Alan Wee-Chung Liew, Brian Lovell, Clinton Fookes, Jun Zhou, Yongsheng Gao, Michael Blumenstein, and Zhiyong Wang, ed. DICTA 2016. IEEE. 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Gold Coast, Australia. Nov 2016, pp. 156-163.
- Ma, F., Yu, L., Bajger, M. and Bottema, M.J. (2015). Mammogram mass classification with temporal features and multiple kernel learning. In Proceedings of DICTA 2015. IEEE Xplore. 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Adelaide, Australia. Nov 2015, pp. 505-511.

[10.1109/DICTA.2015.7371282] - Sajeev, S., Bajger, M. and Lee, G.N. (2015). Segmentation of Breast Masses in Local Dense Background using Adaptive Clip Limit-CLAHE. In Proceeedings of DICTA 2015. IEEE Xplore. 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Adelaide. Nov 2015, pp. 669-676.
- Lee, G. and Bajger, M. (2014). Statistical temporal changes for breast cancer detection: a preliminary study. In Hiroshi Fujita, Takeshi Hara, Chisako Muramatsu, ed. Lecture Notes in Computer Science, Vol. 8539: Breast Imaging. Netherlands: Springer. 12th International Workshop on Breast Imaging, IWDM 2014. Gifu City, Japan. Jun 2014, pp. 635-642.

[10.1007/978-3-319-07887-8] [Scopus] - 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) Acta Press. Signal Processing, Pattern Recognition and Applications (SPPRA 2012) Crete, Greece. Jun 2012, pp. 43-50.

[10.2316/P.2012.778-050] [Scopus] - Bottema, M., Bajger, M., Williams, S. and Ma, F. (2012). Mathematics in medical image analysis: a focus on mammography. In W Wahyuni, IE Mijayanti & D Rosadi, ed. Proceedings of the 6th SEAMS-GMU International Conference on Mathematics and Its Applications. Yogyakarta, Indonesia: Universitas Gadjah Mada. Mathematics and Its Applications in the Development of Sciences and Technology. Yogyakarta, Indonesia. Jul 2011, pp. 51-64.
- 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. Canada: ACTA Press. Ninth IASTED International Conference on Biomedical Engineering, BioMed 2012. Innsbruck, Austria. Feb 2012, pp. 199-206.

[10.2316/P.2012.764-052] [Scopus] - 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. Germany: Springer-Verlag Berlin. International Workshop on Digital Mammography. Girona, Spain. Jun 2010, pp. 752-759.

[Scopus] - Bajger, M., Ma, F., Williams, S. and Bottema, M.J. (2010). Mammographic mass detection with statistical region merging. In Proceedings: DICTA 2010. USA: IEEE. Digital Image Computing: Techniques and Applications. Sydney, NSW. Dec 2010, pp. 27-32.

[Scopus] - 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. USA: IEEE Computer Society. Digital Image Computing Techniques and Applications. Melbourne, Australia. Dec 2009, pp. 400-407.

[10.1109/DICTA.2009.72] [Scopus] - 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. USA: IEEE Computer Society. Digital Image Computing Techniques and Applications. Melbourne, Australia. Dec 2009, pp. 236-241.

[10.1109/DICTA.2009.47] [Scopus] - 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) Berlin: Springer. 9th International Workshop on Digital Mammography. Tucson, AZ, USA. Jul 2008, pp. 158-165.

[10.1007/978-3-540-70538-3_23] [Scopus] - 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. Los Alamitos, CA: IEEE. 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI08) Paris, France. May 2008, pp. 89-92.

[10.1109/ISBI.2008.4540939] [Scopus] - Ma, F., Bajger, M. and Bottema, M.J. (2007). Robustness of two methods for segmenting salient features in screening mammograms. In Proceedings of DICTA. Los Alamitos, USA: IEEE. 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA) Glenelg, SA. Dec 2007, pp. 112-117.

[10.1109/DICTA.2007.4426784] [Scopus] - 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. Berlin: Springer. 8th International Workshop, IWDM 2006. Manchester, UK. Jun 2006, pp. 642-649.

[10.1007/11783237_86] [Scopus] - 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. Berlin, Germany: Springer. 11th Asia-Pacific Conference, ACSAC 2006. Shanghai, China. Sep 2006, pp. 6-23.

[10.1007/11859802_3] [Scopus] - 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. St Lucia, Queensland, Australia: University of Queensland Press. APRS Workshop on Digital Image Computing. Griffith University, Brisbane, Australia. Feb 2005.
- 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. Danvers, USA: Institute of Electrical and Electronic Engineers. Digital Image Computing Techniques and Applications 2005. Cairns, QLD, Australia. Dec 2005, pp. 47.

[10.1109/DICTA.2005.55] [Scopus]

- Saha, R., Bajger, M. and Lee, G.N. (2017). Circular shape constrained fuzzy clustering (CiscFC) for nucleus segmentation in Pap smear images.
*Computers in Biology and Medicine,*85 pp. 13-23.

[10.1016/j.compbiomed.2017.04.008] - Ma, F., Yu, L., Bajger, M. and Bottema, M.J. (2015). Incorporation of fuzzy spatial relation in temporal mammogram registration.
*FUZZY SETS AND SYSTEMS,*279(Article: 6780) pp. 87-100.

[10.1016/j.fss.2015.03.021] [Scopus] [Web Link] - Caon, M., Sedlar, J., Bajger, M. and Lee, G. (2014). Computer-assisted segmentation of CT images by statistical region merging for the production of voxel models of anatomy for CT dosimetry.
*Australasian Physical and Engineering Sciences in Medicine,*37 pp. 393-403.

[10.1007/s13246-014-0273-x] [Scopus] - 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.

[Scopus] [Web Link] - 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.

[10.1007/s11265-007-0140-z] [Scopus] - 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.

[10.1016/j.patcog.2006.12.011] [Scopus] - Bajger, M. (2004). On the composite Pexider equation modulo a subgroup.
*Publicationes Mathematicae-Debrecen,*64(1-2) pp. 39-61.

[Scopus] - Bajger, M. (1998). On generalized Cauchy and Pexider functional equations over a field.
*Glasnik Matematicki,*33(53) pp. 239-249. - Bajger, M. (1998). On the structure of some flows on the unit circle.
*Aequationes mathematicae,*55 pp. 106-122.

[Scopus] - Bajger, M. (1997). A generalized Pexider equation.
*ACTA MATHEMATICA HUNGARICA,*75(1-2) pp. 43-54.

[Scopus] - Bajger, M. (1997). Iterative Pexider equation modulo a subset.
*Aequationes mathematicae,*53 pp. 155-161.

[Scopus] - Bajger, M. (1996). On a generalized Pexider equation connected with the iteration theory.
*Publicationes Mathematicae-Debrecen,*48(1-2) pp. 77-88. - Bajger, M. (1995). Increasing solution of the translation equation.
*Opuscula Mathematica,*15 pp. 33-37. - Bajger, M. (1994). Iterative Pexider equation.
*Publicationes Mathematicae-Debrecen,*44(1-2) pp. 67-77.

- Saha, R., Bajger, M. and Lee, G.N. (2017). Circular shape constrained fuzzy clustering (CiscFC) for nucleus segmentation in Pap smear images.
*Computers in Biology and Medicine,*85 pp. 13-23.

[10.1016/j.compbiomed.2017.04.008] - Ma, F., Yu, L., Bajger, M. and Bottema, M.J. (2015). Incorporation of fuzzy spatial relation in temporal mammogram registration.
*FUZZY SETS AND SYSTEMS,*279(Article: 6780) pp. 87-100.

[10.1016/j.fss.2015.03.021] [Scopus] [Web Link] - Caon, M., Sedlar, J., Bajger, M. and Lee, G. (2014). Computer-assisted segmentation of CT images by statistical region merging for the production of voxel models of anatomy for CT dosimetry.
*Australasian Physical and Engineering Sciences in Medicine,*37 pp. 393-403.

[10.1007/s13246-014-0273-x] [Scopus] - 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.

[Scopus] [Web Link] - 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.

[10.1007/s11265-007-0140-z] [Scopus] - 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.

[10.1016/j.patcog.2006.12.011] [Scopus] - Bajger, M. (2004). On the composite Pexider equation modulo a subgroup.
*Publicationes Mathematicae-Debrecen,*64(1-2) pp. 39-61.

[Scopus] - Bajger, M. (1998). On generalized Cauchy and Pexider functional equations over a field.
*Glasnik Matematicki,*33(53) pp. 239-249. - Bajger, M. (1998). On the structure of some flows on the unit circle.
*Aequationes mathematicae,*55 pp. 106-122.

[Scopus] - 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.

[10.1007/0-387-28487-7_1] [Scopus]

**Professional memberships**

- Australian Pattern Recognition Society (APRS)
- Association for Computing Machinery (ACM)
- Australian Mathematical Society

**Journal reviewer (**verified by Publons**)**

- IEEE Journal of Biomedical and Health Informatics
- Australasian Physical and Engineering Sciences in Medicine
- Biomedical Signal Processing and Control
- IEEE Transactions on Information Technology in Biomedicine
- Computers in Biology and Medicine
- Pattern Recognition Letters
- Sensors
- Remote Sensing
- other

- Computer Aided Screening Mammography
- Image Analysis

Dr
Mariusz
Bajger
Flinders University
https://www.flinders.edu.au/people/mariusz.bajger

Phone: | +61 8 82013984 |

Email: | |

Location: | Tonsley (4.09) |

Postal address: | GPO Box 2100, Adelaide 5001, South Australia |

**Currently supervised (or co-supervised) research projects**

*Feature generation and selection for classification of ROI's in mammography images of dense breasts*(Sagar Shrestha, MIT project)*Effects of preprocessing on CNN analysis of breast cancer histopathology images*(Kevin Clark, Honours project)*Segmentation methods for digital imaging using shape priors*(Ratna Saha, PhD candidate)*Efficient texture descriptors for detection of masses in dense regions of mammograms*(Shelda Sajeev, PhD candidate)

Students interested in research towards Honours, Master or PhD degree in the areas outlined in the projects please contact Mariusz by email/phone. Other research projects in the area of Medical Image Analysis/Pattern Recognition may also be available.