A two-phase decision support framework for the automatic screening of digital fundus images

被引:10
作者
Antal, Balint [1 ]
Hajdu, Andras [1 ]
Maros-Szabo, Zsuzsanna [2 ]
Torok, Zsolt [2 ]
Csutak, Adrienne [2 ]
Peto, Tuende [3 ,4 ]
机构
[1] Univ Debrecen, Fac Informat, POB 12, H-4010 Debrecen, Hungary
[2] Univ Debrecen, Med & Hlth Sci Ctr, H-4032 Debrecen, Hungary
[3] Moorfields Eye Hosp NHS Fdn Trust, NIHR Biomed Res Ctr Ophthalmol, London EC1V 2PD, England
[4] UCL Inst Ophthalmol, London EC1V 2PD, England
关键词
Biomedical image processing; Medical decision-making; Medical expert systems; DIABETIC-RETINOPATHY;
D O I
10.1016/j.jocs.2012.01.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper we give a brief review on the present status of automated detection systems describe for the screening of diabetic retinopathy. We further detail an enhanced detection procedure that consists of two steps. First, a pre-screening algorithm is considered to classify the input digital fundus images based on the severity of abnormalities. If an image is found to be seriously abnormal, it will not be analysed further with robust lesion detector algorithms. As a further improvement, we introduce a novel feature extraction approach based on clinical observations. The second step of the proposed method detects regions of interest with possible lesions on the images that previously passed the pre-screening step. These regions will serve as input to the specific lesion detectors for detailed analysis. This procedure can increase the computational performance of a screening system. Experimental results show that both two steps of the proposed approach are capable to efficiently exclude a large amount of data from further processing, thus, to decrease the computational burden of the automatic screening system. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:262 / 268
页数:7
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