Algorithms for automatic segmentation of bovine embryos produced in vitro

2nd International Conference on Mathematical Modeling in Physical Sciences 2013

物理学;数学

Melo, D.H.^1 ; Nascimento, M.Z.^2 ; Oliveira, D.L.^1 ; Neves, L.A.^3 ; Annes, K.^4

Center of Mathematics, Computing and Cognition, Federal University of ABC (UFABC), Santo-André SP, Brazil^1

Faculty of Computing, Federal University of Uberlândia (UFU), Uberlândia, MG, Brazil^2

Institute of Biosciences, Letters and Science, Department of Computer Science and Statistics, São Paulo State University (UNESP), São José do Rio Preto, SP, Brazil^3

Laboratory of Cellular and Molecular Biology, Center of Natural Sciences and Humanities, Federal University of ABC (UFABC), Santo-André SP, Brazil^4

关键词: Anisotropic filters;    Automatic segmentations;    Connected component;    Histological images;    Segmentation methods;    Statistical measures;    Thresholding techniques;    Unsupervised segmentation method;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/490/1/012125/pdf
DOI  :  10.1088/1742-6596/490/1/012125

来源: IOP

【 摘 要 】

In vitro production has been employed in bovine embryos and quantification of lipids is fundamental to understand the metabolism of these embryos. This paper presents a unsupervised segmentation method for histological images of bovine embryos. In this method, the anisotropic filter was used in the differents RGB components. After pre-processing step, the thresholding technique based on maximum entropy was applied to separate lipid droplets in the histological slides in different stages: early cleavage, morula and blastocyst. In the postprocessing step, false positives are removed using the connected components technique that identify regions with excess of dye near pellucid zone. The proposed segmentation method was applied in 30 histological images of bovine embryos. Experiments were performed with the images and statistical measures of sensitivity, specificity and accuracy were calculated based on reference images (gold standard). The value of accuracy of the proposed method was 96% with standard deviation of 3%.