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- W4367011766 abstract "Ophthalmic disorders like glaucoma, diabetic retinopathy, hypertension can be easily identified by examining the vascular structure of the retina. This makes vessel segregation of fundus images very important for the detection and diagnosis of similar diseases. There are challenges, especially given a large amount of noise and the diverse structures of thin vessels. This article has created an innovative approach to the extraction of vascular structures for the detection and diagnosis of a wide variety of eye diseases. First, we use a variety of image processing techniques to help you extract the features you need. The next step is to build the model using the Extreme Gradient Boosting algorithm using the data extracted from different techniques earlier. All of these models are tested on other image sets and an accuracy rating is calculated. A larger model is prepared based on the accuracy rating. From that the less significant features are removed without compromising the performance. The model results are analyzed using standard scoring parameters and prove to be one of the best in the class." @default.
- W4367011766 created "2023-04-27" @default.
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- W4367011766 date "2023-01-01" @default.
- W4367011766 modified "2023-09-25" @default.
- W4367011766 title "Feather-Light Vessel Segregation Model" @default.
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- W4367011766 doi "https://doi.org/10.1007/978-981-19-5191-6_48" @default.
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