Automated Classification of Glandular Tissue by Statistical Proximity Sampling
المؤلفون المشاركون
Simonsson, Martin
Bengtsson, Ewert
Azar, Jimmy C.
Hast, Anders
المصدر
International Journal of Biomedical Imaging
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-01-18
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Due to the complexity of biological tissue and variations in staining procedures, features that are based on the explicit extraction of properties from subglandular structures in tissue images may have difficulty generalizing well over an unrestricted set of images and staining variations.
We circumvent this problem by an implicit representation that is both robust and highly descriptive, especially when combined with a multiple instance learning approach to image classification.
The new feature method is able to describe tissue architecture based on glandular structure.
It is based on statistically representing the relative distribution of tissue components around lumen regions, while preserving spatial and quantitative information, as a basis for diagnosing and analyzing different areas within an image.
We demonstrate the efficacy of the method in extracting discriminative features for obtaining high classification rates for tubular formation in both healthy and cancerous tissue, which is an important component in Gleason and tubule-based Elston grading.
The proposed method may be used for glandular classification, also in other tissue types, in addition to general applicability as a region-based feature descriptor in image analysis where the image represents a bag with a certain label (or grade) and the region-based feature vectors represent instances.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Azar, Jimmy C.& Simonsson, Martin& Bengtsson, Ewert& Hast, Anders. 2015. Automated Classification of Glandular Tissue by Statistical Proximity Sampling. International Journal of Biomedical Imaging،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1065287
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Azar, Jimmy C.…[et al.]. Automated Classification of Glandular Tissue by Statistical Proximity Sampling. International Journal of Biomedical Imaging No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1065287
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Azar, Jimmy C.& Simonsson, Martin& Bengtsson, Ewert& Hast, Anders. Automated Classification of Glandular Tissue by Statistical Proximity Sampling. International Journal of Biomedical Imaging. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1065287
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1065287
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