A Clinicopathological Study of Various Oral Cancer Diagnostic Techniques.

Oral cancer is one of the most commonly occurring malignant tumors in the head and neck regions with high incident rate and mortality rate in the developed countries than in the developing countries. Generally, the survival rate of cancer patients may increase when diagnosed at early stage, followed by prompt treatment and therapy. Recently, cancer diagnosis and therapy design for a specific cancer patient have been performed with the advanced computer-aided techniques.

A new mathematical modelling based shape extraction technique for Forensic Odontology.

Forensic Odontology is a specific means for identifying a person in which deceased, and particularly in fatality incidents. The algorithm can be proposed to identify a person by comparing both postmortem (PM) and antemortem (AM) dental radiographs and photographs. This work aims to introduce a new mathematical algorithm for photographs in addition with radiographs.

Performance evaluation of maximal separation techniques in immunohistochemical scoring of tissue images.

This paper presents an automatic scoring method for p53 immunostained tissue images of oral cancer that consist of tissue image segmentation, splitting of clustered nuclei, feature extraction and classification. The tissue images are segmented using entropy thresholding technique in which the optimum threshold value to each color component is obtained by maximizing the global entropy of its gray-level co-occurrence matrix and clustered cells are separated by selectively applying marker-controlled watershed transform. Cell nuclei feature is extracted by maximal separation technique (MS) based on blue component of tissue image and subsequently, each cell is classified into one of four categories using multi-level thresholding.

Diagnosis of dental deformities in cephalometry images using support vector machine.

This paper proposes an automated target recognition algorithm using Support Vector Machine (SVM) to extract landmark points for craniofacial features in cephalometry radiograph. The features are extracted by subjecting the radiograph to the Projected Principle Edge Distribution (PPED) algorithm. Edge flags are accumulated in every four columns and spatial distribution of edge flags are represented by a histogram.

Performance analysis of various techniques applied in human identification using dental X-rays.

This paper proposes a novel approach for automating the analysis of identifying the person based on their ante mortem and postmortem reports. This approach involves three techniques (i.e.