Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis

The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis