Automated Extraction of Data for Construction of Parkinson's Disease Experimental Model

Abstract

This paper is devoted to the description of automated method for experimental data acquisition which is required to fill the model of Parkinson's Decease preclinical stage. Digital images of the immunostained brain sections of experimental animals are used as a data source. Proposed method: 1) is based on the following mathematical morphology operations: opening, grayscale reconstruction, closing, bot-hat transformation, morphological gradient, watershed transformation; 2) enables: to smooth heterogeneous complex background; to select small objects on images depending on given sizes and gray values; to eliminate out-of-focus objects; to separate close objects; to calculate features of selected objects; 3) is intended for automatic extraction of dopaminergic neurons terminals on striatum frontal section images. Experimental investigations confirmed that the developed method supports automated processing and analysis of section images.