Convolutional neural network in classifying three stages of age-related macula degeneration
المؤلفون المشاركون
al-Sadi, Inas Hammud
Husayn, Saja Mahdi
al-Sultan, Ali Yaqub
المصدر
Journal of Babylon University : Journal of Applied and Pure Sciences
العدد
المجلد 29، العدد 3 (31 ديسمبر/كانون الأول 2021)، ص ص. 64-79، 16ص.
الناشر
تاريخ النشر
2021-12-31
دولة النشر
العراق
عدد الصفحات
16
التخصصات الرئيسية
العلوم الاقتصادية والمالية وإدارة الأعمال
الملخص EN
Age-related macular degeneration (AMD) is an eye disorder that may blur the clear, central vision you use for things like reading and driving.
It is one of several disorders that influence the retina.
The word "age-related" applies to the reality that it is more prevalent among older persons.
The term "macular" refers to a region of your eye named the macula.
The term "degeneration" refers to the kind of eye injury that occurs.
A disease that affects older people is age-related macular degeneration (AMD).
In AMD, the macula produces a gradual accumulation of yellow deposits named drusen.
Diagnosis with fluorescein angiography allows identifying and locating abnormal vascular processes.
Most ophthalmologists now use consistent optical tomography to diagnose and evaluate follow-up in response to treatment with Avastin or Lucentis, which are injected into the eye's vitreous at different intervals.
Early detection and care, as in other eye disorders, were found to reduce the risk of blindness and vision loss.
Automated retinal examination devices save patients, time, resources, and vision as opposed to manual diagnosis procedures.
The purpose of this study is to suggest an automated method using the Machine Learning (CNN) method to identify patients with macular degeneration AMD using images of the ODIR dataset.
A convolutional neural network (CNN) was applied to extract the deep features from the fundus images present in the data set for the classification of the images to AMD different stages (Early,Intermediate, and Late), beside the Normal status of the eye.
Specificity, Sensitivity, Accuracy, F-score, and Precision metrics were used to estimate classification efficiency the highest accuracy we will get is accuracy: 97%, sensitivity: 98.52%, specificity: 89.29%, area under the curve: 93.9%.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Husayn, Saja Mahdi& al-Sultan, Ali Yaqub& al-Sadi, Inas Hammud. 2021. Convolutional neural network in classifying three stages of age-related macula degeneration. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 29, no. 3, pp.64-79.
https://search.emarefa.net/detail/BIM-1382256
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Husayn, Saja Mahdi…[et al.]. Convolutional neural network in classifying three stages of age-related macula degeneration. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 29, no. 3 (Oct. / Dec. 2021), pp.64-79.
https://search.emarefa.net/detail/BIM-1382256
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Husayn, Saja Mahdi& al-Sultan, Ali Yaqub& al-Sadi, Inas Hammud. Convolutional neural network in classifying three stages of age-related macula degeneration. Journal of Babylon University : Journal of Applied and Pure Sciences. 2021. Vol. 29, no. 3, pp.64-79.
https://search.emarefa.net/detail/BIM-1382256
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Text in English ; abstracts in English and Arabic.
رقم السجل
BIM-1382256
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر