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Medical Image Fusion Based on Feature Extraction and Sparse Representation
المؤلفون المشاركون
المصدر
International Journal of Biomedical Imaging
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-02-21
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods.
However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration.
In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously.
Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information.
SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation.
The decision map is added to the normal sparse representation based method to improve the speed of the algorithm.
Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images.
The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Fei, Yin& Wei, Gao& Zongxi, Song. 2017. Medical Image Fusion Based on Feature Extraction and Sparse Representation. International Journal of Biomedical Imaging،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1159620
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Fei, Yin…[et al.]. Medical Image Fusion Based on Feature Extraction and Sparse Representation. International Journal of Biomedical Imaging No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1159620
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Fei, Yin& Wei, Gao& Zongxi, Song. Medical Image Fusion Based on Feature Extraction and Sparse Representation. International Journal of Biomedical Imaging. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1159620
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1159620
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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