ANUGRAH, MUHAMMAD LUTHFI and Erwin, Erwin (2021) SEGMENTASI PEMBULUH DARAH RETINA PADA PENYAKIT DIABETIC RETINOPATHY MENGGUNAKAN METODE FRACTALNET CONVOLUTIONAL NEURAL NETWORK. Undergraduate thesis, Sriwijaya University.
Text
RAMA_56201_09011181722026.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (11MB) | Request a copy |
|
Preview |
Text
RAMA_56201_09011181722026_0029017101_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (5MB) | Preview |
Text
RAMA_56201_09011181722026_0029017101_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (626kB) | Request a copy |
|
Text
RAMA_56201_09011181722026_0029017101_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (936kB) | Request a copy |
|
Text
RAMA_56201_09011181722026_0029017101_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy |
|
Text
RAMA_56201_09011181722026_0029017101_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (226kB) | Request a copy |
|
Text
RAMA_56201_09011181722026_0029017101_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (440kB) | Request a copy |
|
Text
RAMA_56201_09011181722026_0029017101_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy |
|
Text
RAMA_56201_09011181722026_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (6MB) | Request a copy |
Abstract
The retina is a very crucial organ in the human eye. The retina has a blood vessel section which in every human has a different form of blood vessels. Early detection of retinal disease can be done through sections of the retinal blood vessels. In order to facilitate the medical world in detecting diabetic retinopathy on the retina, a retinal image segmentation study was carried out in order to distinguish between retinal images that have the disease or not. This study presents retinal segmentation using the Fractalnet Convolutional Neural Network method. The first step is to prepare the data used, namely DRIVE. Then proceed with data processing using Color Channel Separation, Grayscale, CLAHE (Contrast Limited Adaptive Histogram Equalization), and data Augmentation. Followed by the segmentation process using the Fractalnet architecture, after that the best model is selected by looking at the parameters. From the results of the research conducted to get the best model with parameters Accuracy value of 96.15%, Sensitivity 74.89%, Specificity 77.49% and F1 Score of 77.01%.
Item Type: | Thesis (Undergraduate) |
---|---|
Uncontrolled Keywords: | Retina, Segmentasi, Fractalnet, Convolutional Neural Network, Diabetic Retinopathy, Augmentasi Data |
Subjects: | Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages |
Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
Depositing User: | Mr. Anugrah Muhammad Luthfi |
Date Deposited: | 01 Dec 2021 06:20 |
Last Modified: | 01 Dec 2021 06:20 |
URI: | http://repository.unsri.ac.id/id/eprint/58418 |
Actions (login required)
View Item |