Wright, D., Stander, J. and Nicolaides, K. (1997) Non- parametric density estimation and discrimination from images of shapes. Journal of the Royal Statistical Society, Series C: Applied Statistics, 46, 365-380.

has been cited by the following article:

• TITLE: Raman spectroscopy for human cancer tissue diagnosis: A pattern recognition approach

  AUTHORS: Maher Rizkalla, Parvin Ghane, Mangilal Agarwal, Sudhir Shrestha, Kody Varahramyan

  KEYWORDS: Cancer; Tissues; Raman Spectroscopy; Pattern Recognition

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.5 No.12A, December 31, 2012

  ABSTRACT: In this work, optical scattering using Raman spectroscopy has been analyzed for various cancer tissues. The Raman shifts obtained at the Indiana University Bloomington (IUB) and Indiana University-Purdue University Indianapolis (IUPUI) laboratories have been processed for diagnosing various types of cancer tissues. The objective of this research is to distinguish between cancerous and non-cancerous tissues. Small size tissue samples have been processed, seeking the minimum size tissue that can be diagnosed via Raman spectroscopy. The tests have been conducted on nearly 20 human tissues. A Matlab program has been written following Parzen-Window classifier to recognize the Raman shift pattern for various types of cancer tissues, including breast cancer, kidney, and Gyn-Uterus. A software visual model has been used for data processing. Unique signals for breast and kidney tumors have been obtained. The approach followed in this paper shows promise for early cancer detection in humans.