首页|A novel method for detection of hard exudates from fundus images based on SVM and improved FCM

A novel method for detection of hard exudates from fundus images based on SVM and improved FCM

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Diabetic retinopathy (DR) is one of the most important causes of visual impairment.Automatic recognition of DR lesions,like hard exudates (EXs),in retinal images can contribute to the diagnosis and screening of the disease.To achieve this goal,an automatically detecting approach based on improved FCM (IFCM) as well as support vector machines (SVM) was established and studied.Firstly,color fundus images were segmented by IFCM,and candidate regions of EXs were obtained.Then,the SVM classifier is confirmed with the optimal subset of features and judgments of these candidate regions,as a result hard exudates are detected from fundus images.Our database was composed of 126 images with variable color,brightness,and quality.70 of them were used to train the SVM and the remaining 56 to assess the performance of the method.Using a lesion based criterion,we achieved a mean sensitivity of 94.65％ and a mean positive predictive value of 97.25％.With an image-based criterion,our approach reached a 100％ mean sensitivity,96.43％ mean specificity and 98.21％ mean accuracy.Furthermore,the average time cost in processing an image is 4.56 s.The results suggest that the proposed method can efficiently detect EXs from color fundus images and it could be a diagnostic aid for ophthalmologists in the screening for DR.

diabetic retinopathyimproved FCMsupport vector machineshard exudatesfundus images

GAO Wei-wei、SHEN Jian-xin、WANG Ming-hong、ZUO Jing

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College of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai 201620, P.R.China

College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P.R.China

Department of Ophthalmology, Jiangsu Province Hospital of TCM, Nanjing 210029, P.R.China

Supported by the National High Technology Research and Development Program of China (863 Program)Fundamental Research Funds for the Central UniversitiesJiangsu Province Science and Technology Support PlanProgram Sponsored for Scientific Innovation Research of College Graduate in Jangsu ProvinceShanghai University Scientific Selection and Cultivation for Outstanding Young Teachers in Special Fund

2006AA020804NJ20120007BE2010652CXLX11_0218ZZGCD15081

2018

重庆大学学报(英文版)
重庆大学

重庆大学学报(英文版)

影响因子：0.02
ISSN：1671-8224
年,卷(期)：2018.17(3)
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