Carcinoma cell identification via optical microscopy and shape feature analysis

Abstract

Optical microscopy is commonly used for cancer cell detection. Focusing on carcinoma cell identification via optical microscopy, a proof-of-concept study was performed at Laboratory of Design, Optimization and Modeling (LCOMS) to determine the grade of cancer cells. This paper focuses on three types of abnormal cells; namely, Benign Hyperplasia (BH), Intraepithe-lial Neoplasia (IN), which is a precursor state for can-cer, and Carcinoma (Ca), which corresponds to ab-normal tissue proliferation cancer. These types of cells were used to assess the efficiency of using shape features to identify carcinoma cells. A comparative study based on performance indicator concludes that three features, Area, Xor-Convex, and Solidity, were found to be effective in identifying the Carcinoma grade of cancer cells.