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Learning-Based Visual Saliency Model for Detecting Diabetic Macular Edema in Retinal Image
المؤلفون المشاركون
Zou, Xiaochun
Zhao, Xinbo
Yang, Yongjia
Li, Na
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-01-14
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
This paper brings forth a learning-based visual saliency model method for detecting diagnostic diabetic macular edema (DME) regions of interest (RoIs) in retinal image.
The method introduces the cognitive process of visual selection of relevant regions that arises during an ophthalmologist’s image examination.
To record the process, we collected eye-tracking data of 10 ophthalmologists on 100 images and used this database as training and testing examples.
Based on analysis, two properties (Feature Property and Position Property) can be derived and combined by a simple intersection operation to obtain a saliency map.
The Feature Property is implemented by support vector machine (SVM) technique using the diagnosis as supervisor; Position Property is implemented by statistical analysis of training samples.
This technique is able to learn the preferences of ophthalmologist visual behavior while simultaneously considering feature uniqueness.
The method was evaluated using three popular saliency model evaluation scores (AUC, EMD, and SS) and three quality measurements (classical sensitivity, specificity, and Youden’s J statistic).
The proposed method outperforms 8 state-of-the-art saliency models and 3 salient region detection approaches devised for natural images.
Furthermore, our model successfully detects the DME RoIs in retinal image without sophisticated image processing such as region segmentation.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zou, Xiaochun& Zhao, Xinbo& Yang, Yongjia& Li, Na. 2016. Learning-Based Visual Saliency Model for Detecting Diabetic Macular Edema in Retinal Image. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1099756
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zou, Xiaochun…[et al.]. Learning-Based Visual Saliency Model for Detecting Diabetic Macular Edema in Retinal Image. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1099756
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zou, Xiaochun& Zhao, Xinbo& Yang, Yongjia& Li, Na. Learning-Based Visual Saliency Model for Detecting Diabetic Macular Edema in Retinal Image. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1099756
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1099756
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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