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, addressing the limitations of manual analysis. It facilitated tasks such as counting hair cells, classifying them into inner and outer hair cells, determining their frequency response based on cochlear location, and generating cochleograms. This tool aimed to provide a fast, unbiased, and comprehensive analysis of cochlear images, overcoming the challenges posed by large imaging datasets. Additionally, HCAT's framework could be adapted for deep-learning-based detection in other biological tissues, offering a versatile solution for image analysis in various research fields.