Automated Glomeruli Quantification

This project is to develop an application to analyze mice brain image and find regions called “Glomeruli” in accessory olfactory bulbs (AOB). The goal of this process is to find an alternative way to manual identification of these regions and find all their properties such as size, color composition and numbers per AOB image section. Since the manual recognition and quantification of glomeruli on digital images is a time-consuming task, we developed a program to identify glomeruli in digital images and quantify the latter properties. The suggested software is an opensource script written in python, which is available in the GitHub webpage.
Glomeruli are neuropil-rich regions of the main or accessory olfactory bulbs (AOB), where the axons of olfactory or vomeronasal neurons and dendrites of mitral/tufted cells form synaptic connections. There are some clues show if the size and number of AOB glomeruli are being analyzed for control and specific type of gene mutated mice, these two types of animals can be distinguished by these quantities (Prince et al. 2013Brignall and Cloutier 2015). These studies show average glomeruli size are much bigger and glomeruli size are much smaller in posterior accessory olfactory bulbs (pAOB) of mutant respect to control type. The goal of our program is to able to find these distinction by analyzing glomeruli automatically.
To shortly introduce the program, this software imports PNG, TIFF and most of lossless image formats and scans whole channels to find glomeruli and analyze their desired properties by using the OpenCV library. Glomeruli are being recognized as the external contours after thresholding input image by “Gaussian Adaptive” method. Below is one of the program output compare to manual selection by a human.


Automated identifying glomeruli. White borders indicate found glomeruli.


Manual identifying glomeruli. White borders indicate found glomeruli.

A graphical user interface (GUI) is also written in LabVIEW programing to interact with the python script. This interface can be compiled for MAC, Windows and Linux operating system. Below is a screenshot of the design GUI.

Program graphical interface (GUI) is writting by LabVIEW programing to interact with python script and analyze images

Quantitative comparison of manual vs. the program’s output demonstrates the ability to distinguish a control from a mutant via by comparing their AOB’s glomeruli size and numbers.


Automated identifying glomeruli. White borders indicate found glomeruli.


Manual identifying glomeruli. White borders indicate found glomeruli.

Description

A Python project to analyse stacked brain images and find AOB glomeruli.

Published: Sep 2021

Language: Python

Source Code: GitHub

Download Paper: Journal Page