Segmentation of immunohistochemical staining of β-catenin expression of oral cancer using EM algorithm

ObjectivesOral Cancer, also called Oral Squamous Cell Carcinoma (OSCC), has been one of the serious cancers that affect the South Asian countries. A range of diagnostic strategies are available including biopsy of the affected part. The Wnt/β-catenin pathway plays important roles in morphogenesis, normal physiological functions, and tumor formation. This study examined the accumulation of β-catenin in the nuclei and cytoplasm of oral cancer.MethodsThe accuracy of histopathological results is hampered by considerable inter and intra-reader variability even by expert pathologists. In order to get both qualitative and quantitative results, we developed a system for diagnosis of oral cancer using Expectation–Maximization (EM algorithm).ResultsThe microscopic images of immunohistochemical staining of β-catenin expression were segmented using Iterative Method of (EM) algorithm to extract the cellular and extracellular components of an image. The segmentation process of the system uses unitone conversion to obtain a single channel image using Principal Component Analysis (PCA) with the highest contrast. Finally, the unitone image is normalized to (0–1) range.ConclusionBased on the segmentation process we conclude that β-catenin expression using EM algorithm is an efficient technique to help the pathologist to evaluate the histological changes on microscopic images of oral cancer.