Optical Screening of Oral Cancer: Technology for Emerging Markets

Oral cancer is the sixth most common cancer in the world. It is one of the most prevalent cancers in the developing countries of South Asia accounting for one third of the world burden. Sixty percent of the cancers are advanced by the time they are detected. Two methods of optical spectroscopy for detection of oral cancer have been discussed here. These methods are simple, easy to handle and noninvasive. The evaluation of the data is done automatically using pattern recognition techniques, making the screening subjective.

[1]  G. Thomas,et al.  Effect of screening on oral cancer mortality in Kerala, India: a cluster-randomised controlled trial , 2005, The Lancet.

[2]  N. Hyde,et al.  Oral cancer: the importance of early referral. , 1999, The Practitioner.

[3]  N Ramanujam,et al.  Fluorescence spectroscopy: a diagnostic tool for cervical intraepithelial neoplasia (CIN). , 1994, Gynecologic oncology.

[4]  C. MacAulay,et al.  A pilot study for a screening trial of cervical fluorescence spectroscopy , 2003, International Journal of Gynecologic Cancer.

[5]  A. Jemal,et al.  Global cancer statistics , 2011, CA: a cancer journal for clinicians.

[6]  C. Krishna,et al.  HPLC-LIF for early detection of oral cancer , 2003 .

[7]  J. Meurman,et al.  Increased salivary acetaldehyde levels in heavy drinkers and smokers: a microbiological approach to oral cavity cancer. , 2000, Carcinogenesis.

[8]  G. Zonios,et al.  Morphological model of human colon tissue fluorescence , 1996, IEEE Transactions on Biomedical Engineering.

[9]  N. Ramanujam Fluorescence spectroscopy of neoplastic and non-neoplastic tissues. , 2000, Neoplasia.

[10]  S. Hecht,et al.  Cigarette smoking: cancer risks, carcinogens, and mechanisms , 2006, Langenbeck's Archives of Surgery.

[11]  W. Jerjes,et al.  Optical techniques in diagnosis of head and neck malignancy. , 2006, Oral oncology.

[12]  D. Winn,et al.  Smoking and drinking in relation to oral and pharyngeal cancer. , 1988, Cancer research.

[13]  David G. Stork,et al.  Pattern Classification , 1973 .

[14]  M. Weinberg,et al.  Assessing oral malignancies. , 2002, American family physician.

[15]  Danny Coomans,et al.  Classification Using Adaptive Wavelets for Feature Extraction , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  J. Ferlay,et al.  Global Cancer Statistics, 2002 , 2005, CA: a cancer journal for clinicians.

[17]  Hiroshi Murase,et al.  Visual learning and recognition of 3-d objects from appearance , 2005, International Journal of Computer Vision.

[18]  P. Notani GLOBAL VARIATION IN CANCER INCIDENCE AND MORTALITY , 2001 .

[19]  G. Rodrigues,et al.  Oral cancer at a glance , 2003 .

[20]  Aapo Hyvärinen,et al.  Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.

[21]  Kumar,et al.  Neural Networks a Classroom Approach , 2004 .