DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy
المؤلفون المشاركون
Iakovidis, D. K.
Koulaouzidis, Anastasios
Vasilakakis, Michael D.
Spyrou, Evaggelos
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-09-03
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Wireless Capsule Endoscopy (WCE) is a noninvasive diagnostic technique enabling the inspection of the whole gastrointestinal (GI) tract by capturing and wirelessly transmitting thousands of color images.
Proprietary software “stitches” the images into videos for examination by accredited readers.
However, the videos produced are of large length and consequently the reading task becomes harder and more prone to human errors.
Automating the WCE reading process could contribute in both the reduction of the examination time and the improvement of its diagnostic accuracy.
In this paper, we present a novel feature extraction methodology for automated WCE image analysis.
It aims at discriminating various kinds of abnormalities from the normal contents of WCE images, in a machine learning-based classification framework.
The extraction of the proposed features involves an unsupervised color-based saliency detection scheme which, unlike current approaches, combines both point and region-level saliency information and the estimation of local and global image color descriptors.
The salient point detection process involves estimation of DIstaNces On Selective Aggregation of chRomatic image Components (DINOSARC).
The descriptors are extracted from superpixels by coevaluating both point and region-level information.
The main conclusions of the experiments performed on a publicly available dataset of WCE images are (a) the proposed salient point detection scheme results in significantly less and more relevant salient points; (b) the proposed descriptors are more discriminative than relevant state-of-the-art descriptors, promising a wider adoption of the proposed approach for computer-aided diagnosis in WCE.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Vasilakakis, Michael D.& Iakovidis, D. K.& Spyrou, Evaggelos& Koulaouzidis, Anastasios. 2018. DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1131817
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Vasilakakis, Michael D.…[et al.]. DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1131817
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Vasilakakis, Michael D.& Iakovidis, D. K.& Spyrou, Evaggelos& Koulaouzidis, Anastasios. DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1131817
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1131817
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