Performance evaluation of different preprocessing techniques for blood vessel extraction in fundus images

Prabhu, Nandana; Bhoir, Deepak; Rao, U.S. Mahadeva

doi:10.1109/icac3.2017.8318765

Cited by 1 publication

(2 citation statements)

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“…For the image to be acceptable for further processing, each photo processing technique requires the completion of a few fundamental procedures. The goal is to create the ideal raw image input for real-time processing [27]. Therefore, prior to any treatment, pictures must be pre-processed [28].…”

Section: Introductionmentioning

confidence: 99%

“…Digital images are represented using different color models. The initial stage in preprocessing might be considered the selection of an appropriate model [27]. In general, the goal of image restoration in image analysis is to relieve human observers of this mission by reconstructing a realistic approximation of the original image from obscuring or noisy observations [28], [29].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Image Enhancement Methods for Diabetic Retinopathy Screening

Toresa,

Wiza,

Anggraini

et al. 2023

J. RESTI (Rekayasa Sist. Teknol. Inf.)

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The most common factor contributing to visual abnormalities that result in blindness is known as diabetic retinopathy (DR). Retinal fundus scanning, a non-invasive method that is integral to the picture pre-processing phase, can be used to identify and monitor DR. Low intensity, irregular lighting, and inhomogeneous color are some of the main issues with DR fundus photographs. Analysis of aberrant characteristics on retinal fundus pictures to identify diabetic retinopathy is one of the key responsibilities of image enhancement. However, a variety of approaches have been created, and it is unknown whether one is best suited for use with retinal fundus images. This study investigated various image enhancement methods in order to see aberrant abnormalities on retinal fundus pictures more clearly. This study investigated various image enhancement methods in order to see aberrant abnormalities on retinal fundus pictures more clearly. Contrast Limited Adaptive Histogram Equalization (CLAHE) method, Gray Level Slicing method, Median Filtering method, and Low Light method are image improvement methods used to enhance retinal fundus images. The parameters Natural Image Quality Evaluator (NIQE), Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and entropy will be used to assess each image enhancement technique's performance. An ophthalmologist from Hospital University Sains Malaysia (HUSM) provided the image data. The findings indicate that while each technique has its own benefits, the CLAHE technique, with a standard deviation MSE of 0.0004, is the best.

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Section: Introductionmentioning

confidence: 99%