E-ISSN 0976-2833 | ISSN 0975-3583
 

Original Research 


Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN)

Elvina Amanda, Marischa Elveny, Rahmad Syah.

Abstract
Diabetic retinopathy and normal retinal diseases need a detection approach, in this case, to make the decision to diagnose diabetic retinopathy through retinal fundus images. The application aims to identify diabetic retinopathy through fundus imagery using Probabilistic Neural Network. The method we use involves the Probabilistic Neural Network (PNN) in the process of testing image data through the retina fundus. The results of this study have achieved detection of the accuracy of recognition of the range in reading images through the retina fundus of 88.9%, and The estimation of σ≥ 0.8 is the best benefit of smoothing boundaries to recognize diabetic retinopathy by utilizing the Probabilistic Neural Network, this shows the detection of research is quite high.

Key words: PNN Method, Retinal Fundus, Image Processing, Diabetic Retinopathy Detection.


 
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Pubmed Style

Elvina Amanda, Marischa Elveny, Rahmad Syah. Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN). J Cardiovasc. Dis. Res.. 2020; 11(4): 302-306. doi:10.31838/jcdr.2020.11.04.54


Web Style

Elvina Amanda, Marischa Elveny, Rahmad Syah. Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN). http://www.jcdronline.org/?mno=17930 [Access: January 15, 2022]. doi:10.31838/jcdr.2020.11.04.54


AMA (American Medical Association) Style

Elvina Amanda, Marischa Elveny, Rahmad Syah. Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN). J Cardiovasc. Dis. Res.. 2020; 11(4): 302-306. doi:10.31838/jcdr.2020.11.04.54



Vancouver/ICMJE Style

Elvina Amanda, Marischa Elveny, Rahmad Syah. Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN). J Cardiovasc. Dis. Res.. (2020), [cited January 15, 2022]; 11(4): 302-306. doi:10.31838/jcdr.2020.11.04.54



Harvard Style

Elvina Amanda, Marischa Elveny, Rahmad Syah (2020) Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN). J Cardiovasc. Dis. Res., 11 (4), 302-306. doi:10.31838/jcdr.2020.11.04.54



Turabian Style

Elvina Amanda, Marischa Elveny, Rahmad Syah. 2020. Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN). Journal of Cardiovascular Disease Research, 11 (4), 302-306. doi:10.31838/jcdr.2020.11.04.54



Chicago Style

Elvina Amanda, Marischa Elveny, Rahmad Syah. "Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN)." Journal of Cardiovascular Disease Research 11 (2020), 302-306. doi:10.31838/jcdr.2020.11.04.54



MLA (The Modern Language Association) Style

Elvina Amanda, Marischa Elveny, Rahmad Syah. "Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN)." Journal of Cardiovascular Disease Research 11.4 (2020), 302-306. Print. doi:10.31838/jcdr.2020.11.04.54



APA (American Psychological Association) Style

Elvina Amanda, Marischa Elveny, Rahmad Syah (2020) Diabetic Retinopathy, The Automated of Detection of Retinal Fundus Images with Probabilistic Neural Networks (PNN). Journal of Cardiovascular Disease Research, 11 (4), 302-306. doi:10.31838/jcdr.2020.11.04.54





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