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Wavelet and multi-fractal based analysis on DIC images in epithelium region to detect and diagnose the cancer progress among different grades of tissues

DIC (Differential Interference Contrast Image) images of cervical pre-cancer tissues are taken from epithelium region, on which wavelet transform and multi-fractal analysis are applied. Discrete wavelet transform (DWT) through Daubechies basis are done for identifying fluctuations over polynomial trends for clear characterization and differentiation of tissues. A systematic investigation of denoised images is carried out through the continuous Morlet wavelet. The scalogram reveals the changes in coefficient peak values from grade-I to grade-III. Wavelet normalized energy plots are computed in order to show the difference of periodicity among different grades of cancerous tissues. Using the multi-fractal de-trended fluctuation analysis (MFDFA), it is observed that the values of Hurst exponent and width of singularity spectrum decrease as cancer progresses from grade-I to grade-III tissue.