Dr Mariusz Bajger

Lecturer

College of Science and Engineering

place Tonsley Building (4.09)
GPO Box 2100, Adelaide 5001, South Australia

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 medical image analysis, data science, network science, image segmentation, digital pathology, computer vision.

Qualifications
PhD Mathematics, University of Queensland, Australia, 1996.
MSc Applied Mathematics, Jagiellonian University, Poland, 1988.
Honours, awards and grants
  • Commission on Excellence and Innovation in Health (CEIH) Grant, 2023
  • Channel 7 Children Research Foundation Grant, 2022
  • Freemason’s Centre for Male Health and Wellbeing Grant, 2021-2022
  • NeuroSurgical Research Foundation Grant, 2020-2021
  • 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.
Topic coordinator
COMP8781 Computer Mathematics GE
ENGR1721 Engineering Programming
ENGR8800 Engineering Programming GE
COMP2781 Computer Mathematics
Topic lecturer
COMP2781 Computer Mathematics
ENGR8800 Engineering Programming GE
ENGR1721 Engineering Programming
COMP8781 Computer Mathematics GE
Supervisory interests
Artificial intelligence and image processing
Medical image analysis
Medical image processing
Pattern recognition
Higher degree by research supervision
Completion
Principal supervisor: Medical Image Analysis (1)
Associate supervisor: Mathematical Modeling (1), Medical Image Analysis (2)
Interests
  • Image Analysis
Further information

Recently supervised (or co-supervised) research projects

  • Developing deep learning algorithms for Gleason grading of prostate cancer (Zhi Lin, BENG Honours)
  • Three-dimensional dual-energy CT baggage scanner image segmentation toolkit (John Dunstan, BENG Honours)
  • Feature generation and selection for classification of ROI's in mammography images of dense breasts (Sagar Shrestha, MIT)
  • Effects of preprocessing on CNN analysis of breast cancer histopathology images (Kevin Clark, BENG Honours)
  • Segmentation methods for digital imaging using shape priors (Ratna Saha, PhD)
  • Efficient texture descriptors for detection of masses in dense regions of mammograms (Shelda Sajeev, PhD)

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

CT Segmentation (png)

Mass Detection in Dense Breasts (png)

Publications (pdf)