A versatile macro-based neurohistological image analysis suite for ImageJ focused on automated and standardized user interaction and reproducible data output

Abstract

BACKGROUND\nIn recent decades, the advent of advanced microscopy techniques, including high resolution digital imaging, multi-dimensional acquisition, and multiple fluorescence channel exposure, as well as the availability of inexpensive terabyte-capacity digital storage, has enabled neuroscience research laboratories to engage in high-throughput quantitative image analysis experiments involving numerous chemical markers and experimental conditions covering multiple brain regions and composed of hundreds of micrographs. Analyzing and processing these large data sets presents challenges in ensuring precision and reproducibility under demanding time and training constraints.\n\n\nNEW METHOD\nWe provide a plugin suite for ImageJ that automates and simplifies user interaction in neurohistological image analysis tasks, including region selection and thresholding, area measurement, point and object counts, and general image processing and review. Our plugin is based on the ImageJ macro language and integrates scripts for administrator maintenance of distributed code and inter-laboratory collaboration over cloud file server clients or local networks.\n\n\nRESULTS\nOur macro-based interface approach integrates dozens of novel techniques, software interactions, algorithm calls, and background tasks into single user commands. Every image analysis run generates image and region records and outputs calibrated data in a standardized, login-based folder structure for investigator review.\n\n\nCOMPARISONS WITH EXISTING METHODS\nOur plugin suite adds extensive functionality not otherwise available for ImageJ or other image analysis packages. The code is free and open source and can be extended by an active community of developers and customized by end-users seeking to integrate existing plugins.\n\n\nCONCLUSIONS\nThis software facilitates functionality and efficiency critical to image analysis-based neurohistological research.