Semi-automated counting model for arbuscular mycorrhizal fungi spores using the Circle Hough Transform and an artificial neural network
AUTOR(ES)
MELO, CLÊNIA A.O. DE
FONTE
An. Acad. Bras. Ciênc.
DATA DE PUBLICAÇÃO
21/10/2019
RESUMO
Abstract: Arbuscular Mycorrhizae (AM) are mutualistic associations between Arbuscular Mycorrhizal Fungi (AMF) and the roots of many plant species. AMF spores give rise to filaments that develop in the root system of plants and contribute to the absorption of water and some nutrients. 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.
Documentos Relacionados
- Evaluation of a semi-automated platelet-counting system.
- An inexpensive semi-automated sequence reader for the Apple II computer.
- Semi-automated Phalanx Bone Segmentation Using the Expectation Maximization Algorithm
- Semi-automated method for the differential determination of plasma catecholamines
- Semi-Automated method for the differential determination of plasma catecholamines