Super-Resolution Based Automatic Diagnosis of Retinal Disease Detection for Clinical Applications
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Super‑Resolution Based Automatic Diagnosis of Retinal Disease Detection for Clinical Applications V. Anoop1 · P. R. Bipin2
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract In medical image processing, the automatic analysis of pathology localization and the anatomical segmentation steps are more important. The Fundus images of Low resolution (LR) are not applicable to detect the retinal disease. The main aim of this paper is to enhance the resolution of the low-resolution retinal images obtained from the cheap imaging devices within less computational time and high accuracy. So, we proposed the fundus image with Super-Resolution and its performance via the Diagnostically Significant Area (DSA). This approach focuses only on the region of Interest (ROI) instead of concentrating on the entire image leading to less computational time by reducing the time complexity. Therefore, the Eigen MR inter-band feature, Energy MR intra-band feature, Shannon entropy and Sensitive Contrast Interest (SCI) are used to capture the clinical data from the selected region. Therefore, the DSA is determined by using Levenshtein based KNN classifier. Because of better classification outcomes, the Bicubic method is employed in the selected region to reduce the loss of reconstruction error. Experimentally, the implementation works are carried out in the platform of MATLAB with DRIVE and STARE database images are chosen. The super-resolution image performances are compared with different start of art techniques such as PSM, GR-SR, LLE, and SpC-SR. Finally, higher efficiency with low computational super-resolution fundus images is collected. Keywords Retinal image · Super-resolution · ROI · Fundus · KNN
1 Introduction The degeneration of age-related muscular, Diabetic Retinopathy (DR) disease and the retinal problem diagnosis are carried out by using Fluorescein Angiographic (FA). In the diabetic population, the main reason for the blindness and low vision is Diabetic Macular Edema (DME). When compared to Proliferative diabetic retinopathy, the DME contains more visual loss. For ophthalmologists, the diagnosis and prediction of various eye diseases from the muscular area is an important task [1]. Hence, progressive disease is * V. Anoop [email protected]; [email protected] 1
Jyothi Engineering College, Cheruthuruthy, Thrissur, Kerala 679531, India
2
Adi Shankara Institute of Engineering and Technology, Kalady, Ernakulam, Kerala 683574, India
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V. Anoop, P. R. Bipin
monitored and corrected via the diagnosis of the small vessels with structural and functional evaluation. Moreover, the illnesses in eyesight like glaucoma, macular edema, and age-related macular degeneration are diagnosed by using the network of microvascular and the structure of retinal analysis [2]. By using scanning laser ophthalmoscope or fundus camera is to collect the retinal image. The fundus image of retinal analysis of diseases is critical detection. The increasing availability of screening retinal contains
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