The Hair Cell Analysis Toolbox: A Machine Learning-Based Whole Cochlea Analysis Pipeline

The Hair Cell Analysis Toolbox (HCAT) was developed as a machine learning-based software to automate the analysis of auditory hair cells in the cochlea. It addressed the need for fast, unsupervised, and unbiased image analysis, overcoming the limitations of manual counting and classification of hair cells. HCAT automated tasks such as counting hair cells, classifying them into inner and outer hair cells, determining their best frequency, and generating cochleograms. This tool significantly improved the efficiency and comprehensiveness of cochlear image analysis and could be adapted for deep-learning-based detection in other biological tissues.