Locally Adaptive Operators for Red Lesions Detection in Eye Fundus Images.

Autor: Bagesteiro LD; Universidade Federal do Pampa, RS, Brasil., Welfer D; Department of Applied Computing, Universidade Federal de Santa Maria, Santa Maria, RS, Brasil., Cordeiro d'Ornellas M; Department of Applied Computing, Universidade Federal de Santa Maria, Santa Maria, RS, Brasil., Kazienko JF; Colégio Técnico Industrial de Santa Maria, Universidade Federal de Santa Maria, Santa Maria, RS, Brasil., Pereira Haygert CJ; Department of Clinical Medicine - Santa Maria University Hospital - Federal University of Santa Maria (UFSM), Rio Grande do Sul, Brasil., Dotto GN; Department of Clinical Medicine - Santa Maria University Hospital - Federal University of Santa Maria (UFSM), Rio Grande do Sul, Brasil.
Jazyk: angličtina
Zdroj: Studies in health technology and informatics [Stud Health Technol Inform] 2017; Vol. 245, pp. 289-293.
Abstrakt: One of the major features required by automated software tools of screening for diabetic retinopathy is the detection of red lesions. This paper presents a new automatic method in order to locate red lesions in color eye fundus images. The method relies on mathematical morphology operators and has a coarse and a fine detection stages, respectively. The former detection stage detects structures of low-intensity values in the retina, such as microaneurysms, hemorrhages, blood vessels and the fovea center. Additionally, the latter stage proposes to improve the detection of red lesions identified in the previous stage. For experiments, we use the well-known publicly available DIARETDB1 database. The results indicate that our method detected red lesions with 75.81% and 93.48% of mean sensitivity and mean specificity, respectively.
Databáze: MEDLINE