2023
DOI: 10.3390/sym15020287
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Development of a Computer System for Automatically Generating a Laser Photocoagulation Plan to Improve the Retinal Coagulation Quality in the Treatment of Diabetic Retinopathy

Abstract: In this article, the development of a computer system for high-tech medical uses in ophthalmology is proposed. An overview of the main methods and algorithms that formed the basis of the coagulation plan planning system is presented. The system provides the formation of a more effective plan for laser coagulation in comparison with the use of existing coagulation techniques. An analysis of monopulse- and pattern-based laser coagulation techniques in the treatment of diabetic retinopathy has shown that modern t… Show more

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Cited by 6 publications
(3 citation statements)
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“…Furthermore, the accuracy of the proposed method surpasses that of Al-Bander [5] and is slightly below Song [9], which employs a deep learning approach, achieving an accuracy of 98.24% compared to 96.6% and 100%, respectively. However, the proposed method is able to perform well on datasets that have a small number of images such as DRIVE and DiaretDB1, which is not shown in both deep learning models.…”
Section: Discussionmentioning
confidence: 81%
See 1 more Smart Citation
“…Furthermore, the accuracy of the proposed method surpasses that of Al-Bander [5] and is slightly below Song [9], which employs a deep learning approach, achieving an accuracy of 98.24% compared to 96.6% and 100%, respectively. However, the proposed method is able to perform well on datasets that have a small number of images such as DRIVE and DiaretDB1, which is not shown in both deep learning models.…”
Section: Discussionmentioning
confidence: 81%
“…Measuring the distance between the hard exudates and the fovea is crucial for evaluating the severity of DME and necessitates precise detection methods [4]. Additionally, the computational efficiency of the utilized computer-assisted diagnosis techniques significantly impacts the speed of the overall process [5].…”
Section: Introductionmentioning
confidence: 99%
“…A computer-aided diagnosis (CAD) system [2,3] involves leveraging computer-generated outputs as support tools for clinicians to make medical diagnoses. The urgently needed functionality in current CAD systems for histopathological slide images is the binary classification of pathology images into benign and malignant categories, followed by subclassification within these categories.…”
Section: Introductionmentioning
confidence: 99%