Semi-automated counting model for arbuscular mycorrhizal fungi spores using the Circle Hough Transform and an artificial neural network.

This article introduces a semi-automated counting model of AMF spores in slide images based on Artificial Neural Network (ANN). The semi-automated counting of AMF spores facilitates and accelerates the tasks of researchers, who still do the AMF spore counting manually. We built a representative database of spore images, processing images through the Circle Hough Transform (CHT) method and training an ANN to classify patterns automatically. The classification analysis and the performances of the proposed method against the manual method are presented in this paper. The accuracy for the identification of spores by CHT in conjunction to ANN classification in the images was 90%. The results indicate that this method can accurately detect the presence of AMF spores in images as well as count them with a high level of confidence. PMID: 31644640 [PubMed - in process]
Source: An Acad Bras Cienc - Category: Science Authors: Tags: An Acad Bras Cienc Source Type: research