Sparse Codebook Model of Local Structures for Retrieval of Focal Liver Lesions Using Multiphase Medical Images
المؤلفون المشاركون
Chen, Yen-Wei
Wang, Jian
Han, Xian-Hua
Xu, Yingying
Lin, Lanfen
Hu, Hongjie
Jin, Chongwu
المصدر
International Journal of Biomedical Imaging
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-02-13
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Characterization and individual trait analysis of the focal liver lesions (FLL) is a challenging task in medical image processing and clinical site.
The character analysis of a unconfirmed FLL case would be expected to benefit greatly from the accumulated FLL cases with experts’ analysis, which can be achieved by content-based medical image retrieval (CBMIR).
CBMIR mainly includes discriminated feature extraction and similarity calculation procedures.
Bag-of-Visual-Words (BoVW) (codebook-based model) has been proven to be effective for different classification and retrieval tasks.
This study investigates an improved codebook model for the fined-grained medical image representation with the following three advantages: (1) instead of SIFT, we exploit the local patch (structure) as the local descriptor, which can retain all detailed information and is more suitable for the fine-grained medical image applications; (2) in order to more accurately approximate any local descriptor in coding procedure, the sparse coding method, instead of K-means algorithm, is employed for codebook learning and coded vector calculation; (3) we evaluate retrieval performance of focal liver lesions (FLL) using multiphase computed tomography (CT) scans, in which the proposed codebook model is separately learned for each phase.
The effectiveness of the proposed method is confirmed by our experiments on FLL retrieval.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Jian& Han, Xian-Hua& Xu, Yingying& Lin, Lanfen& Hu, Hongjie& Jin, Chongwu…[et al.]. 2017. Sparse Codebook Model of Local Structures for Retrieval of Focal Liver Lesions Using Multiphase Medical Images. International Journal of Biomedical Imaging،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1159601
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Jian…[et al.]. Sparse Codebook Model of Local Structures for Retrieval of Focal Liver Lesions Using Multiphase Medical Images. International Journal of Biomedical Imaging No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1159601
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Jian& Han, Xian-Hua& Xu, Yingying& Lin, Lanfen& Hu, Hongjie& Jin, Chongwu…[et al.]. Sparse Codebook Model of Local Structures for Retrieval of Focal Liver Lesions Using Multiphase Medical Images. International Journal of Biomedical Imaging. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1159601
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1159601
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