Multifractal analysis for detection of different stages in cervical cancer from colposcopy images

Abstract

Cervical cancer is of significant health concern globally, particularly in developing countries where access to advanced healthcare facilities and medical resources is limited, leading to increased mortality rates. The gold standard for diagnosing CIN (cervical intraepithelial neoplasia) and invasive cervical cancer involves performing a colposcopy-guided biopsy followed by a pathological diagnosis. However, its effectiveness is challenged by limited sensitivity in distinguishing between various stages of cervical cancer, especially in regions where there is a shortage of skilled colposcopists and insufficient access to medical resources. This study presents a method for categorizing infectious, pre-cancerous, and cancerous conditions through the application of multifractal analysis, specifically two dimensional multifractal detrended fluctuation analysis (2D MFDFA), using images obtained through colposcopy. The utilization of multifractal parameters, namely the generalized Hurst exponent and the width of the singularity spectrum, in the analysis distinctly demonstrated variations among the infectious, precancerous, and cancerous conditions. Therefore, it offers valuable insights to healthcare professionals, assisting in the accurate classification and effective management of cervical cancer using Hurst exponent and multifractal spectrum width.