Automatic corneal tissue classification using bag-of-visual-words approaches

Abstract Corneal confocal microscopy is a promising diagnostic
method for peripheral neuropathy. It allows the recording of
the sub-basal nerve plexus (SNP) and enables the morphological
analysis of peripheral nerves. This work evaluates classification
models for real-time evaluation of cornea images in order to find
suitable methods for an automatic focus adaptation to the SNP.
The analyzed Bag-of-Visual-Words method leads to models with
an accuracy of 0.9, even on a small training dataset, and a runtime
of 18 ms per image. Furthermore, the analysis of the support
vector machine real-valued output shows high potential for
the implementation of real-time focus optimization methods.