Supervised Automation of Cell Counting in Confocal Microscopic Cochlear Imaging Datasets Using Macro in Imaris

Analyzing confocal microscopic data of biological samples using the Imaris software poses challenges due to its time-consuming nature involving tedious multiple steps and possibility of human errors. Here, we developed a supervised automation protocol to minimize manual input in cell and spot counting on confocal images obtained from mouse cochlear sections. The protocol increases efficiency by incorporating image recognition and object-oriented macros. Moreover, the protocol being adaptable allows scientists in diverse other fields to customize it for their specific needs.