Automated identification of keratinization and keratin pearl area from in situ oral histological images

• In histological evaluation of OSCC, keratinization plays a major role.
• Proposed CAD system automates quantification of keratinization at 4× magnification.
• Keratinized area in MSB plane of Db component is enhanced.
• Chan–Vese model based segmentation achieves 95.08% accuracy w.r.t. ground truths.
• A quantitative measure is proposed for OSCC grading (PDOSCC, MDOSCC, WDOSCC).

Oral squamous cell carcinoma (OSCC) has contributed 90% of oral cancer worldwide. In situ histological evaluation of tissue sections is the gold standard for oral cancer detection. Formation of keratinization and keratin pearl is one of the most important histological features for OSCC grading. This paper aims at developing a computer assisted quantitative microscopic methodology for automated identification of keratinization and keratin pearl area from in situ oral histological images. The proposed methodology includes colour space transform in YDbDr channel, enhancement of keratinized area in most significant bit (MSB) plane of Db component, segmentation of keratinized area using Chan–Vese model. The proposed methodology achieves 95.08% segmentation accuracy in comparison with (manually) experts-based ground truths. In addition, a grading index describing keratinization area is explored for grading OSCC cases (poorly, moderately and well differentiated).

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