Application of S-Transform on Hyper kurtosis based Modified Duo Histogram Equalized DIC images for Pre-cancer Detection

TL;DR

This paper presents a novel approach combining hyper kurtosis based histogram equalization and S-transform analysis to improve pre-cancer detection in DIC images by highlighting tissue inhomogeneity and structural variations.

Contribution

It introduces a new method integrating hyper kurtosis histogram equalization with S-transform for enhanced tissue analysis in pre-cancer detection.

Findings

Enhanced contrast in DIC images improves tissue differentiation.

S-transform reveals amplitude spectrum variations correlating with tissue roughness.

Method effectively distinguishes different stages of DIC tissues.

Abstract

Our proposed hyper kurtosis based histogram equalized DIC images enhances the contrast by preserving the brightness. The evolution and development of precancerous activity among tissues are studied through S-transform (ST). The significant variations of amplitude spectra can be observed due to increased medium roughness from normal tissue were observed in time-frequency domain. The randomness and inhomogeneity of the tissue structures among human normal and different grades of DIC tissues is recognized by ST based timefrequency analysis. This study offers a simpler and better way to recognize the substantial changes among different stages of DIC tissues, which are reflected by spatial information containing within the inhomogeneity structures of different types of tissue.