Automated gold particle quantification of immunogold labeled micrographs

Journal of Neuroscience Methods
Rune Enger

Abstract

Immunogold cytochemistry is the method of choice for precise localization of antigens on a subcellular scale. The process of immunogold quantification in electron micrographs is laborious, especially for proteins with a dense distribution pattern. Here I present a MATLAB based toolbox that is optimized for a typical immunogold analysis workflow. It combines automatic detection of gold particles through a multi-threshold algorithm with manual segmentation of cell membranes and regions of interests. The automated particle detection algorithm was applied to a typical immunogold dataset of neural tissue, and was able to detect particles with a high degree of precision. Without manual correction, the algorithm detected 97% of all gold particles, with merely a 0.1% false-positive rate. To my knowledge, this is the first free and publicly available software custom made for immunogold analyses. The proposed particle detection method compares favorably to previously published algorithms. The software presented here will be valuable tool for researchers in neuroscience working with immunogold cytochemistry.

Citations

Oct 12, 2018·Glia·Md Mahdi Hasan-OlivePer Kristian Eide
Aug 9, 2019·Journal of Neuropathology and Experimental Neurology·Md Mahdi Hasan-OlivePer Kristian Eide
Apr 10, 2021·Scientific Reports·Diego JerezMichael S Smirnov

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