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CIHR Skin Research Training Centre
Core Mentors: Dr. Tim Lee
Tim Lee, PhD
Senior Scientist, Cancer Control Research Program, BC Cancer Agency
Assistant professor, Department of Dermatology and Skin Science, University of British Columbia
Associate Member, Biomedical Engineering Program, University of British Columbia
Associate Member, School of Population and Public Health, University of British Columbia
Adjunct professor, the School of Computing Science, Simon Fraser University

675 W 10th Ave., Vancouver, BC V5Z 1L3
Telephone: 604-675-8053
Fax: 604-675-8180
Website: http://www.bccrc.ca/dept/cc/tim-lee
Email: tlee@bccrc.ca


1980 BSc, University of British Columbia
1983 MSc, University of British Columbia
2001 PhD, Simon Fraser University

Grant Support

BC Health Research Foundation
Canadian Dermatology Foundation
Canadian Institutes of Health Research
Canadian Partnership Against Cancer
Michael Smith Foundation for Health Research
National Institutes of Health
Natural Sciences and Engineering Research Council of Canada

Research interest

My research interests focus on the development of early diagnostic tools for skin cancer and the investigation of etiology and risk factors of the disease.
1. Early detection tools: Because of low diagnostic sensitivity and specificity for melanoma among the non-dermatologists, there is an urgent need in developing diagnostic tools, especially for primary care providers who first screen patients with possible malignancy. I have been designing automatic computer algorithms to extract key diagnostic features from colour skin images captured by an inexpensive optical technique, dermoscopy, which is used by dermatologists with special training for the technique. Added intelligence from the computer programs could potentially extend the use of the technique to primary care providers.
I am also investigating automated computer algorithms to enumerate and track pigmented skin lesions over time from total body photographs. This type of computer program will help dermatologists to manage high risk melanoma patients and etiologic studies of melanoma.
Although dermoscopy is an effective method for diagnosing melanoma, the technique cannot be used to evaluate skin surface roughness, which is also an important diagnostic parameter. To complement the technique, I initiated another line of research on laser speckle, an optical technique analyzing the skin surface using the backscattered coherent light. Recently, I also investigated how to extract skin internal properties such as bulk optical properties using laser speckle techniques.
2. Etiology and risk factor studies: In the epidemiologic research area, I led the case-control studies on analysing sun behaviour of melanoma patients and on physical activities and melanoma risk. I am also involved in a wide range of studies investigating skin cancer trends, cancer risk due to sun exposure and tanning beds, sunscreen use and the genesis of nevus (the precursor of melanoma), and other diseases. Currently, I am the principal investigator of a case-control study, sponsored by CIHR, examining the relationship among blood levels of organochlorine compounds, UV radiation and melanoma. It is well-known that the main environmental risk factor for melanoma is the UV from sun exposure. However, it is unclear whether the UV is the only factor. Our recent pilot study suggested that organochlorine compounds were highly associated with melanoma even after adjusting for sun exposure. The current CIHR case-control study will test the hypothesis that organochlorine compounds act as a promoter for the disease.  

Selected recent publications

  1. Tchvialeva L, Dhadwal G, Lui H, Kaila S, Zeng H, McLean DI, Lee TK. Polarization speckle imaging as a potential technique for in vivo skin cancer detection. Journal of Biomedical Optics. 2013 June issue.
  2. Sadeghi M, Lee TK, McLean D, Lui H, Atkins MS. Oriented pattern analysis for streak detection in dermoscopy images. Lecture Notes in Computer Science, 2012;7510:298-306.
  3. Mirzaalian H, Lee TK, Hamarneh G. Uncertainty-based feature learning for skin lesion matching using a high order MRF optimization framework. Lecture Notes in Computer Science 2012;7511:98-105.
  4. McLean DI, Phillips N, Zhou Y, Gallagher R, Lee TK. Forty Year Trends in Skin Cancer in British Columbia Canada; 1973-2003. Journal of Cutaneous Medicine and Surgery, 2012 Mar-Apr; 16(2):83-91.
  5. Mirzaalian H, Lee TK, Hamarneh G. Learning features for streak detection in dermoscopic color images using localized radial flux of principal intensity curvature. Proceedings of IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, Breckenridge, Colorado, USA, Jan. 9-10, 2012, page 97-101.
  6. KhakAbi S, Lee TK, Atkins MS. Tree structured model of skin lesion growth pattern via color based cluster analysis. Lecture Notes in Computer Science, 2011;7009:291-299.
  7. Wighton P, Lee TK, Mori G, Lui H, McLean DI, Atkins MS. Conditional random fields and supervised learning in automated skin lesion diagnosis. International Journal of Biomedical Imaging 2011; Article ID 846312, 10 pages. DOI:10.1155/2011/846312
  8. Tchvialeva L, Markhvida I, Lee TK. Error analysis for polychromatic speckle contrast measurements. Optics and Lasers in Engineering. 2011;49:1397-1401.
  9. Wighton P, Lee TK, Lui H, McLean DI, Atkins MS. Generalizing common tasks in automated skin lesion diagnosis. IEEE Transactions on Information Technology in Biomedicine. 2011;15(4):622-629.
  10. Wighton P, Lee TK, Lui H, McLean DI, Atkins MS. Chromatic aberration correction – An enhancement to the calibration of low cost digital dermoscopes. Skin Research and Technology. 2011;17:339-347.
  11. Gallagher RP, MacArthur AC, Lee TK, Weber J-P, Leblanc A, Elwood JM, Borugian M, Spinelli JJ. Plasma levels of polychlorinated biphenyls and risk of cutaneous malignant melanoma: A preliminary study. Int J Cancer. 2011;128(8):1872-1880.
  12. Sadeghi M, Razmara M, Lee TK, Atkins SM. A novel method for detection of pigment network in dermoscopic images using graphs. Computerized Medical Imaging and Graphics. 2011;35(2):137-143.
  13. Tchvialeva L, Markhvida I, Zeng H, McLean DI, Lui H, Lee TK. Surface roughness measurement by speckle contrast under the illumination of light with arbitrary spectral profile. Optics and Lasers in Engineering. 2010;48:774-778.
  14. Wighton P, Sadeghi M, Atkins MS, Lee TK. A fully automatic random walker segmentation for skin lesions in a supervised setting. Lecture Notes in Computer Science, 2009;5762:1108-1115. PubMed ID: 20426222
  15. Mirzaalian H, Hamarneh G, Lee TK. A graph-based approach to skin mole matching incorporating template-normalized coordinates. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2009, Miami Beach, Florida, June 20-26, 2009:2152-2159.
  16. Lee TK, MacArthur AC, Gallagher PR, Elwood JM. Occupational physical activity and risk of malignant melanoma: the Western Canada Melanoma Study. Melanoma Research. 2009;19:260-266.
  17. Drew MS, Lee TK, Rova A. Shape retrieval with eigen-CSS search. Image and Vision Computing. 2009;27:748–755.Tchvialeva L, Lee TK, Markhvida I, McLean DI, Lui H, Zeng H. Using a zone model to incorporate the influence of geometry on polychromatic speckle contrast. Optical Engineering. 2008;47(7):074201.
  18. Tchvialeva L, Lee TK, Markhvida I, McLean DI, Lui H, Zeng H. Using a zone model to incorporate the influence of geometry on polychromatic speckle contrast. Optical Engineering. 2008;47(7):074201.

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