Stochastic Approach for the Identification of Retinopathy of Prematurity

被引:1
作者
Prabakar, Srinivasan [1 ]
Porkumaran, Karantharaj [2 ]
Karthikeyan, R. [3 ]
Isaac, Samson [4 ]
Kannan, Ramani [5 ]
Nor, Nursyarizal Mohd [5 ]
Elamvazuthi, Irraivan [5 ]
机构
[1] Sona Coll Technol, Salem, India
[2] Sri Sairam Inst, Chennai, Tamil Nadu, India
[3] Dr NGP Inst Technol, Coimbatore, Tamil Nadu, India
[4] Karunya Inst Technol & Sci, Coimbatore, Tamil Nadu, India
[5] Univ Teknol PETRONAS, Seri Iskandar, Perak, Malaysia
来源
2020 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT AND ADVANCED SYSTEMS (ICIAS) | 2021年
关键词
ANFIS; CLAHE; retina; ROP; watershed transform; PLUS DISEASE; TORTUOSITY; WIDTH;
D O I
10.1109/ICIAS49414.2021.9642618
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Retinopathy of Prematurity (ROP) is a retinal vessel growth condition that affects premature infants who usually are under a birth weight of 1,500 grams and have a gestational age of 32 weeks or less. The back portion of the eye, retina captures light and sends signals to the brain, creating the vision of eye. Blood vessels supply oxygen and nutrients to the retina and these blood vessels begin to develop at 16-18 weeks after conception, and complete with full maturity before the normal birth. Premature birth suffers the development of the retina vasculature and leaves some of the retina without blood vessels, which causes of visual loss in childhood. Serial RetCam images are acquired from premature infants. By applying three pre-processing techniques such as green colour plane, histogram equalization, Contrast Limited Adaptive Histogram Equalization (CLAHE), we can get the best contrast between the vessels and background of retina. After segmentation, watershed transform is applied, and then six statistical features are taken out from that image. Finally the images are categorized as normal or abnormal by using ANFIS (The Adaptive Neuro-Fuzzy Inference System) classifier.
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页数:6
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