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/.
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. [online]. Available from:
http://dx.doi.org/10.1016/j.cmpb.2008.04.003.
Lee, G.N. and Bottema, M.J. (2006). Significance of classification scores subsequent to feature selection.
Pattern Recognition Letters, 27(14), pp.1702-1709. [online]. Available from:
http://dx.doi.org/10.1016/j.patrec.2006.03.012.
Refereed conference papers
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.
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
12th International Conference on Control, Automation, Robotics and Vision. 12th International Conference on Control, Automation, Robotics and Vision. pp. 1431-1436. [online]. Available from:
http://dx.doi.org/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. 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.
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. 10th International Workshop on Digital Mammography. pp. 636-642.
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. International Conference on Medical Biometrics. pp. 296-305.
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). 10th International Workshop on Digital Mammography (IWDM2010). pp. 636-642.
Show all publications
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/.
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. [online]. Available from:
http://dx.doi.org/10.1016/j.cmpb.2008.04.003.
Lee, G.N. and Bottema, M.J. (2006). Significance of classification scores subsequent to feature selection.
Pattern Recognition Letters, 27(14), pp.1702-1709. [online]. Available from:
http://dx.doi.org/10.1016/j.patrec.2006.03.012.
Refereed conference papers
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.
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
12th International Conference on Control, Automation, Robotics and Vision. 12th International Conference on Control, Automation, Robotics and Vision. pp. 1431-1436. [online]. Available from:
http://dx.doi.org/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. 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.
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. 10th International Workshop on Digital Mammography. pp. 636-642.
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. International Conference on Medical Biometrics. pp. 296-305.
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). 10th International Workshop on Digital Mammography (IWDM2010). pp. 636-642.
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. 95th Scientific Assembly and Annual Meeting, Radiological Society of North America (RSNA). pp. 1082-1082.
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. 95th Scientific Assembly and Annual Meeting, Radiological Society of North America (RSNA). pp. 928-928.
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. 95th Scientific Assembly and Annual Meeting, Radiological Society of North America (RSNA). pp. 607-607.
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. 9th International Workshop on Digital Mammography. 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. SPIE Medical Imaging 2008. pp. 6915141-6915149. [online]. Available from:
http://spie.org/x648.html?product_id=736858.
Lee, G.N. and Fujita, H. (2007). K-means clustering for classifying unlabelled MRI data. In Proceedings of Digital Imaging Computing Techniques and Applications. Digital Imaging Computing Techniques and Applications (DICTA 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. SPIE Medical Imaging 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.
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. 8th International Workshop on Digital Mammography. 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. (2004). 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. WDIC 2003. pp. 105-110.
Journal articles
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.
Conference publications
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.
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. 25th International Congress and Exhibition, Computer Assisted Radiology and Surgery (CARS 2008). pp. S432-S433.
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