Automated whole slide morphometry of sural nerve biopsy using machine learning

The morphometry of sural nerve biopsies, such as fibre diameter and myelin thickness, helps us understand the underlying mechanism of peripheral neuropathies. However, in current clinical practice, only a portion of the specimen is measured manually because of its labour-intensive nature. In this study, we aimed to develop a machine learning-based application that inputs a whole slide image (WSI) of the biopsied sural nerve and automatically performs morphometric analyses.