Manuel E Gegundez-Arias1, Diego Marin2, Beatriz Ponte3, Fatima Alvarez4, Javier Garrido5, Carlos Ortega5, Manuel J Vasallo6, Jose M Bravo6. 1. Department of Mathematics, University of Huelva, Spain. 2. Department of Electronic, Computer Science and Automatic Engineering, University of Huelva, Spain. Electronic address: diego.marin@diesia.uhu.es. 3. Virgen de Macarena University Hospital of Seville, Andalusian Health Service, Spain. 4. Juan Ramon Jimenez Hospital of Huelva, Andalusian Health Service, Spain. 5. North Area of Sanitary Management of Cordoba, Andalusian Health Service, Spain. 6. Department of Electronic, Computer Science and Automatic Engineering, University of Huelva, Spain.
Abstract
AIM: This paper presents a methodology and first results of an automatic detection system of first signs of Diabetic Retinopathy (DR) in fundus images, developed for the Health Ministry of the Andalusian Regional Government (Spain). MATERIAL AND METHODS: The system detects the presence of microaneurysms and haemorrhages in retinography by means of techniques of digital image processing and supervised classification. Evaluation was conducted on 1058 images of 529 diabetic patients at risk of presenting evidence of DR (an image of each eye is provided). To this end, a ground-truth diagnosis was created based on gradations performed by 3 independent ophthalmology specialists. RESULTS: The comparison between the diagnosis provided by the system and the reference clinical diagnosis shows that the system can work at a level of sensitivity that is similar to that achieved by experts (0.9380 sensitivity per patient against 0.9416 sensitivity of several specialists). False negatives have proven to be mild cases. Moreover, while the specificity of the system is significantly lower than that of human graders (0.5098), it is high enough to screen more than half of the patients unaffected by the disease. CONCLUSION: Results are promising in integrating this system in DR screening programmes. At an early stage, the system could act as a pre-screening system, by screening healthy patients (with no obvious signs of DR) and identifying only those presenting signs of the disease.
AIM: This paper presents a methodology and first results of an automatic detection system of first signs of Diabetic Retinopathy (DR) in fundus images, developed for the Health Ministry of the Andalusian Regional Government (Spain). MATERIAL AND METHODS: The system detects the presence of microaneurysms and haemorrhages in retinography by means of techniques of digital image processing and supervised classification. Evaluation was conducted on 1058 images of 529 diabeticpatients at risk of presenting evidence of DR (an image of each eye is provided). To this end, a ground-truth diagnosis was created based on gradations performed by 3 independent ophthalmology specialists. RESULTS: The comparison between the diagnosis provided by the system and the reference clinical diagnosis shows that the system can work at a level of sensitivity that is similar to that achieved by experts (0.9380 sensitivity per patient against 0.9416 sensitivity of several specialists). False negatives have proven to be mild cases. Moreover, while the specificity of the system is significantly lower than that of human graders (0.5098), it is high enough to screen more than half of the patients unaffected by the disease. CONCLUSION: Results are promising in integrating this system in DR screening programmes. At an early stage, the system could act as a pre-screening system, by screening healthy patients (with no obvious signs of DR) and identifying only those presenting signs of the disease.
Authors: D Marin; M E Gegundez-Arias; B Ponte; F Alvarez; J Garrido; C Ortega; M J Vasallo; J M Bravo Journal: Med Biol Eng Comput Date: 2018-01-10 Impact factor: 2.602