On the research work leading to automatic detection of optic disc from retinal images is very essential and crucial for expert ophthalmologists to diagnose diseases. Many of techniques can achieve good performance on retinal feature that is clearly visible. Unfortunately, it is a normal situation that the color retinal images in Thailand are poor-quality images. The existing algorithm cannot detected poor-quality images. Therefore, this study is a part of larger efforts to develop a novel method for detection of optic disc in poorquality retinal images. A novel method is presented towards the development for detection of optic disc in poor-quality retinal images. The digital retinal images are detected by using morphological method and Otsu's algorithm after the key preprocessing steps, i.e., color normalization, contrast enhancement and noise removal. This enables the difference in the proposed method compared to other approaches and the algorithm can achieve good performance even on poor-quality retinal images. The proposed method was evaluated using the local dataset and the publicly available of the STARE project's dataset. The optic disc was detected correctly in 91.35% using the STARE dataset and 97.61% using the local dataset. This system intends to help expert ophthalmologists in screening process to detect of optic disc faster and more easily. General TermsMedical Image Processing
The article that you are looking for is unavailable to public domain. The article is subjected to compliance with 2014-2015 IJCA scientific data guidelines. You might want to navigate the journal via the menu options provided in the left side of the screen. However, feel free to contact us anytime regarding any article which you are unable to find.
Nowadays, the retinal imaging technology has been widely used for segmenting and detecting the exudates in diabetic retinopathy patients. Unfortunately, the retinal images in Thailand are poorquality images. Therefore, detecting of exudates in a large number by screening programs, are very expensive in professional time and may cause human error. In this study, the clinical applications for detection of exudates from the poor quality retinal image are presented. An application incorporating function, including retinal color normalization, contrast enhancement, noise removal, color space selection and removal of the optic disc, was also designed to standardize the workflow of retinal analysis. Afterward, detection of exudate based on optimal global thresholding and improved adaptive Otsu's algorithm was applied. Two experiments were conducted to validate the detection performance with local databases and a publicly available DIARETDB1 database. The first experiment showed the average sensitivity, specificity and accuracy of 93.8, 95.3 and 94.9%, respectively. The cross validation results of the second experiment, 60% (53) of the retinal images were used for training and 40% (36) for testing, the sensitivity, specificity and accuracy are 84.2, 85.9 and 85.2%, respectively. This result indicates the proposed clinical application provides an effective tool in the screening of exudates.
A 70-year-old man was unable to move both eyes to the left side. Ocular motility examination revealed an esotropia and left gaze paralysis. Jugulo-digastric lymph node and bulging nasopharyngeal roof were also observed. A brain MRI revealed a mass involving cavernous sinus, clivus, prepontine cistern and the lower pons. Pathologic examination of the tissue biopsied from the nasopharynx revealed a non-keratinizing squamous cell carcinoma. He was treated with radiotherapy 6600 cGy at tumor and 6600 cGy at the neck node. The neck mass and deficit of the right eye adduction deficit improved but the left eye abduction persisted.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.