Position/s

Lecturer
School of Computer Science, Engineering and Mathematics

Deputy Director of Studies in Mathematics and Statistics
School of Computer Science, Engineering and Mathematics

Qualifications

PhD, Flinders University

MSc, RMIT

Honours, awards and grants

  • Channel 7 Children's Research Foundation grant, 2012-2013
  • Lyn Wrigley Breast Cancer Research & Development Fund, Breast Cancer Research Grant, 2010
  • Certificate of Merit Award, Education Exhibit Category, 95th RSNA (Radiologic Society of North America) meeting, 2009
  • Excellence in Design Award, Education Exhibit Category, 92nd RSNA meeting, 2006
  • JSPS (Japan Society for Promotion of Sciences) International Post-doctoral Fellowship, 2005-2007
  • The Doreen McCarthy, Barbara Crase, Cathy Candler and Brenda Nettle Scholarships 2000

Topic Coordinator:

Topic Lecturer:

Research expertise

  • Artificial intelligence and image processing
  • Statistics

Research interests

My primary research areas are Computer-Aided-Diagnosis (CAD), Medical Image Analysis, Statistical Pattern Recognition and statistical issues related to radiologic studies. More specifically, my research focuses on CAD on breast cancer detection in screening mammograms, whole-body CT segmentation, computational human anatomy, and construction of human voxel models for radiation dose calculation.

Supervisory interests

  • Medical image analysis
  • Statistics

RHD research supervision

Current

Principal supervisor : Medical Image Analysis (1) ;

Associate supervisor : Medical Image Analysis and Computer Science (2) ;

Publications

  • 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.
  • Grim, J. and Lee, G.N. (2012). Evaluation of Screening Mammograms by Local Structural Mixture Models. In T Hobza, ed. Proceedings of the International Conference on Stochastic and Physical Monitoring Systems. Czech RepublicStochastic and Physical Monitoring Systems 2012. Zlenice, Czech Republic. Jun 2012, pp. 51-61.
    [Web Link]
  • 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.
  • Fukuoka, D., Morita, T., Muramatsu, C., Hara, T., Fujita, H. and Lee, G.N. (2009). Automated recognition and registration of breast lesions in whole breast ultrasound data and screening mammography. In RSNA, ed. 95th Scientific Assembly and Annual Meeting Program, Radiological Society of North America. Chicago , USA: Radiological Society of North America (RSNA). 95th Scientific Assembly and Annual Meeting, Radiological Society of North America (RSNA) Chicago, USA. Nov 2009, pp. 928-928.
    [Web Link]
  • Lee, G.N. and Branford, A.J. (2009). Bias in radiologic studies: a review. In RSNA, ed. 95th Scientific Assembly and Annual Meeting Program, Radiological Society of North America. Chicago , USA: Radiological Society of North America. 95th Scientific Assembly and Annual Meeting, Radiological Society of North America (RSNA) Chicago, USA. Nov 2009, pp. 1082-1082.
  • Lee, G.N., Morita, T., Fukuoka, D., Muramatsu, C., Hara, T. and Fujita, H. (2009). Differentiation of mass lesions in whole breast ultrasound images: Volumetric analysis. In RSNA, ed. 95th Scientific Assembly and Annual Meeting Program, Radiological Society of North America. Chicago , USA: Radiological Society of North America (RSNA). 95th Scientific Assembly and Annual Meeting, Radiological Society of North America (RSNA) Chicago, USA. Nov 2009, pp. 607-607.
    [Web Link]
  • Lee, G.N., Kanematsu, M., Kato, H., Kondo, H., Fujita, H. and Hoshi, H. (2008). K-means clustering and classification of diffuse disease based on unlabelled ROI data. In Heinz U. Lemke, ed. International Journal of Computer Assisted Radiology and Surgery. Germany: Springer Berlin/Heidelberg. 25th International Congress and Exhibition, Computer Assisted Radiology and Surgery (CARS 2008) Barcelona, Spain. Jun 2008, pp. S432-S433.
    [10.1007/s11548-008-0207-8]
  • Lee, G.N., Fukuoka, D., Morita, T. and Fujita, H. (2010). Whole-breast ultrasound brings significant screening benefits. Diagnostic Imaging Asia-Pacific, Winter2010 pp. 7-9.
    [Web Link]
  • 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. Springer. 12th International Workshop on Breast Imaging, IWDM 2014. Gifu City, Japan. Jun 2014, pp. 635-642.
  • 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]
  • Li, X., Williams, S., Lee, G. and Deng, M. (2012). Computer-aided mammography classification of malignant mass regions and normal regions based on novel texton features. In CC Cheah, D Sun, Y Hong, S Li, K-A Toh & J Wang, ed. 12th International Conference on Control, Automation, Robotics and Vision. Piscataway, USA: IEEE. ICARV 2012. Guangzhou, China. Jul 2012, pp. 1431-1436.
    [10.1109/ICARCV.2012.6485399]
  • 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]
  • Fujita, H., You, J., Li, Q., Arimura, H., Tanaka, R., Sanda, S., et al. (2010). State-of-the-Art of Computer-Aided Detection/Diagnosis. In David Zhang; Milan Sonka, ed. Medical Biometrics. New York: Springer. International Conference on Medical Biometrics. Hong Kong. Jun 2010, pp. 296-305.
  • Lee, G.N., Okada, T., Fukuoka, D., Hara, T., Morita, T., Takada, E., et al. (2010). Classifying Breast Masses in Volumetric Whole Breast Ultrasound Data: A 2.5-Dimensional Approach. In Digital Mammography: 10th International Workshop on Digital Mammography. Berlin/Heidelberg: Springer. 10th International Workshop on Digital Mammography. Girona, Catalonia, Spain. Jun 2010, pp. 636-642.
    [Web Link]
  • Lee, G.N., Okada, T., Fukuoka, D., Muramatsu, C., Hara, T., Morita, T., et al. (2010). Breast cancer detection in anisotropic ultrasound images. In J. Martf et al., ed. Digital Mammography:10th International Workshop on Digital Mammography (IWDM2010) Berlin/Heidelberg: LNCS Springer. 10th International Workshop on Digital Mammography (IWDM2010) pp. 636-642.
  • Lee, G.N., Fukuoka, D., Ikedo, Y., Hara, T. and Fujita, H. (2008). Classification of benign and malignant masses in ultrasound breast image based on geometric and echo features. In E. Krupinski, ed. Digital Mammography: 9th International Workshop on Digital Mammography. USA: Springer. 9th International Workshop on Digital Mammography. Tucson. Jul 2008, pp. 433-439.
  • Lee, G.N., Kanematsu, M., Kato, H., Kondo, H., Zhou, X., Hara, T., et al. (2008). Unsupervised classification of cirrhotic livers using MRI data. In M. L. Giger & N. Karssemeijer, ed. Proceedings of SPIE Medical Imaging 2008: Computer-Aided Diagnosis. Bellingham, USA: SPIE. SPIE Medical Imaging 2008. San Diego, USA. Feb 2008, pp. 6915141-6915149.
    [Web Link]
  • Lee, G.N. and Fujita, H. (2007). K-means clustering for classifying unlabelled MRI data. In Proceedings of Digital Imaging Computing Techniques and Applications. USA: IEEE Computer Society. Digital Imaging Computing Techniques and Applications (DICTA 2007) Adelaide, Australia. Nov 2007, pp. 92-98.
  • Lee, G.N., Uchiyama, Y., Zhang, X., Kanematsu, M., Zhou, X., Hara, T., et al. (2007). Classification of cirrhotic liver in Gadolinium-enhanced MR images. In Proceedings of SPIE Medical Imaging 2007: Computer-Aided Diagnosis. USA: SPIE. SPIE Medical Imaging 2007. San Diego, USA. Feb 2007, pp. 6514301-6514308.
  • Lee, G.N., Bottema, M.J., Hara, T. and Fujita, H. (2006). Effect of quantisation on co-occurrence matrix based texture features: An example study in mammography. In Proceedings of SPIE Medical Imaging 2006: Computer-Aided Diagnosis. SPIE Medical Imaging 2006, pp. 614451-614459.
    [10.1117/12.653256]
  • Lee, G.N., Hara, T. and Fujita, H. (2006). Classifying masses as benign or malignant based on co-occurrence matrix textures: a comparison study of different gray level quantization. In Digital Mammography: 8th International Workshop on Digital Mammography. UK: Springer. 8th International Workshop on Digital Mammography. Manchester, UK. Jun 2006, pp. 332-339.
  • Lee, G.N., Zhang, X., Kanematsu, M., Zhou, X., Hara, T., Kato, H., et al. (2006). Classification of cirrhotic liver on MR images using texture analysis. In International Journal of Computer Assisted Radiology and Surgery. 20th International Congress and Exhibition, Computer Assisted Radiology and Surgery (CARS 2008) pp. 379-381.
  • Lee, G.N. and Bottema, M.J. (2005). Classification of ROI as invasive lobular carcinoma or normal. In Digital Mammography:7th International Workshop on Digital Mammography. 7th International Workshop on Digital Mammography, pp. 640-645.
  • Lee, G.N. and Bottema, M.J. (2003). Statistical significance of Az scores: classification of masses in screening mammograms as benign or malignant based on high dimensional texture feature space. In Lovell, B. CMeader, A. J, ed. Proceedings of the 2003 APRS Workshop on Digital Image Computing. Brisbane, Australia: University of Queensland Press. WDIC 2003. Brisbane, QLD. Feb 2003, pp. 105-110.
  • 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.
  • 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]
  • Ikedo, Y., Morita, T., Fakuoka, D., Hara, T., Lee, G., Fujita, H., et al. (2009). Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience. International Journal of CARS, 4(3) pp. 299-306.
  • Fujita, H., Uchiyama, Y., Nakagawa, T., Fukuoka, D., Hatanaka, Y., Hara, T., et al. (2008). Computer-aided diagnosis: the emerging of three CAD systems induced by Japanese health care needs. Computer Methods and Programs in Biomedicine, 92(3) pp. 238-248.
    [10.1016/j.cmpb.2008.04.003] [10.1016/j.cmpb.2008.04.003] [Scopus]
  • Lee, G.N. and Bottema, M.J. (2006). Significance of classification scores subsequent to feature selection. Pattern Recognition Letters, 27(14) pp. 1702-1709.
    [10.1016/j.patrec.2006.03.012] [10.1016/j.patrec.2006.03.012] [Scopus]
  • 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. Springer. 12th International Workshop on Breast Imaging, IWDM 2014. Gifu City, Japan. Jun 2014, pp. 635-642.
  • 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]
  • 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]
  • Li, X., Williams, S., Lee, G. and Deng, M. (2012). Computer-aided mammography classification of malignant mass regions and normal regions based on novel texton features. In CC Cheah, D Sun, Y Hong, S Li, K-A Toh & J Wang, ed. 12th International Conference on Control, Automation, Robotics and Vision. Piscataway, USA: IEEE. ICARV 2012. Guangzhou, China. Jul 2012, pp. 1431-1436.
    [10.1109/ICARCV.2012.6485399]
  • Lee, G.N., Okada, T., Fukuoka, D., Muramatsu, C., Hara, T., Morita, T., et al. (2010). Breast cancer detection in anisotropic ultrasound images. In J. Martf et al., ed. Digital Mammography:10th International Workshop on Digital Mammography (IWDM2010) Berlin/Heidelberg: LNCS Springer. 10th International Workshop on Digital Mammography (IWDM2010) pp. 636-642.
  • 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.
  • 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]
  • Ikedo, Y., Morita, T., Fakuoka, D., Hara, T., Lee, G., Fujita, H., et al. (2009). Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience. International Journal of CARS, 4(3) pp. 299-306.
  • Fujita, H., Uchiyama, Y., Nakagawa, T., Fukuoka, D., Hatanaka, Y., Hara, T., et al. (2008). Computer-aided diagnosis: the emerging of three CAD systems induced by Japanese health care needs. Computer Methods and Programs in Biomedicine, 92(3) pp. 238-248.
    [10.1016/j.cmpb.2008.04.003] [10.1016/j.cmpb.2008.04.003] [Scopus]
  • Lee, G.N. and Bottema, M.J. (2006). Significance of classification scores subsequent to feature selection. Pattern Recognition Letters, 27(14) pp. 1702-1709.
    [10.1016/j.patrec.2006.03.012] [10.1016/j.patrec.2006.03.012] [Scopus]

Professional and community engagement

Wildlife Conservation and Biological Data Analysis
Gobert collaborates with researchers at the Adelaide Zoo on the Conservation Program. Her interests include analyzing biological data to help managing and protecting Australian wildlife such as wombats and bird surveys.

Journal Reviewer/ Conference Session Chair
Gobert serves as a reviewer for the Academic Radiology and the Australasian Physical & Engineering Sciences in Medicine.
She served as Session Chairs for the 9th IASTED International Conference on Biomedical Engineering, Innsbruck, 2012 and for the Australian and New Zealand Industrial and Applied Mathematics conference (ANZIAM), Rotorua, New Zealand, 2014. She was a member of  the Technical Committee for the International Conference on digital Image Computing: Techniques and Applications (DICTA), Adelaide, 2007

Professional Memberships

  • The Australian Pattern Recognition Society (APRS)
  • Australian and New Zealand Industrial and Applied Mathematics (ANZIAM)
  • Australian Mathematical Society (AustMS)
  • Statistical Society of Australia, Inc (SSAI)

Contact

Add to address book
Phone: +61 8 82012410
Email:
Location: Information, Science & Technology (237)
Postal address: GPO Box 2100, Adelaide 5001, South Australia

Further information

Prospective PHD students: email gobert.lee@flinders.edu.au

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Current Projects in Medical Image Analysis/Statistical Pattern Recognition

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