Incorporating Privileged Genetic Information for Fundus Image Based Glaucoma Detection

Author(s):  
Lixin Duan ◽  
Yanwu Xu ◽  
Wen Li ◽  
Lin Chen ◽  
Damon Wing Kee Wong ◽  
...  
Author(s):  
Ayushi Agarwal ◽  
Shradha Gulia ◽  
Somal Chaudhary ◽  
Malay Kishore Dutta ◽  
Radim Burget ◽  
...  

Author(s):  
Anindita Septiarini ◽  
Hamdani Hamdani ◽  
Dyna Marisa Khairina

<p>Glaucoma is the second leading cause of blindness in the world; therefore the detection of glaucoma is required. The detection of glaucoma is used to distinguish whether a patient's eye is normal or glaucoma. An expert observed the structure of the retina using fundus image to detect glaucoma. In this research, we propose feature extraction method based on cup area contour using fundus images to detect glaucoma. Our proposed method has been evaluated on 44 fundus images consisting of 23 normal and 21 glaucoma. The data is divided into two parts: firstly, used to the learning phase and secondly, used to the testing phase. In order to identify the fundus images including the class of normal or glaucoma, we applied Support Vector Machines (SVM) method. The performance of our method achieves the accuracy of 94.44%.</p>


Author(s):  
S. Vanakovarayan ◽  
R. Sarath Kumar ◽  
S. Chinnapparaj ◽  
S. Satheesh Kumar

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