Automatic Segmentation of Exudates in Ocular Images using Ensembles of Aperture Filters and Logistic Regression

19th Argentinean Bioengineering Society Congress

Benalcázar, Marco^1,2,3 ; Brun, Marcel^3 ; Ballarin, Virginia^3

Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina^1

Secretaria Nacional de Educacion Superior, Ciencia, Tecnologia e Innovacion Ecuador, Argentina^2

Grupo de Procesamiento Digital de Imágenes, Universidad Nacional de Mar Del Plata, Mar del Plata, Argentina^3

关键词: Automatic segmentations;    Logistic regressions;    Macular edema;    Ocular fundus images;    Ocular images;    Processed images;    Vision loss;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/477/1/012021/pdf
DOI  :  10.1088/1742-6596/477/1/012021

来源: IOP

【 摘 要 】

Hard and soft exudates are the main signs of diabetic macular edema (DME). The segmentation of both kinds of exudates generates valuable information not only for the diagnosis of DME, but also for treatment, which helps to avoid vision loss and blindness. In this paper, we propose a new algorithm for the automatic segmentation of exudates in ocular fundus images. The proposed algorithm is based on ensembles of aperture filters that detect exudate candidates and remove major blood vessels from the processed images. Then, logistic regression is used to classify each candidate as either exudate or non-exudate based on a vector of 31 features that characterize each potensial lesion. Finally, we tested the performance of the proposed algorithm using the images in the public HEI-MED database.