Wavelet Based Classification for Cancer Diagnosis

— We make use of discrete wavelets to extract distinguishing features between normal and cancerous human breast tissue fluorescence spectra. These are then used in conjunction with discriminant analysis for the purpose of reliable tissue differentiation. The wavelet coefficients at different levels of decomposition, representing intensity variations at different scales, are selected as feature vectors wherein the multiresolution and localization properties of wavelets are optimally exploited for identifying features. This wavelet based approach, when combined with the sensitive polarized fluorescence data, yielded statistically reliable characterization of tissue types for diagnostic purpose. Analysis of a number of data sets belonging to both perpendicular and parallel polarized spectra have led to key distinctions between cancerous, benign and normal tissues. of computer aided diagnostics (CAD)[1]. Amongst various optical methods for tissue diagnostics, fluorescence spectroscopy [2...

• Type: Journal
• Year: 2007
• Where: ENGL
• Authors: Bhadra Mani, C. Raghavendra Rao, P. Anantha Lakshmi, Asima Pradhan, Prasanta K. Panigrahi
• Keywords: ENGL 2007, Fluorescence, Tissue Fluorescence, Wavelet