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Enhancing Automatic Classification of Hepatocellular Carcinoma Images through Image Masking, Tissue Changes, and Trabecular Features
المؤلفون المشاركون
Abe, Tokiya
Yamashita, Yoshiko
Kiyuna, Tomoharu
Hashiguchi, Akinori
Abdul Aziz, Maulana
Kanazawa, Hiroshi
Murakami, Yuri
Kimura, Fumikazu
Yamaguchi, Masahiro
Sakamoto, Michiie
Saito, Akira
Ishikawa, Masahiro
Kobayashi, Naoki
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-2، 2ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-12-17
دولة النشر
مصر
عدد الصفحات
2
التخصصات الرئيسية
الملخص EN
Hepatocellular carcinoma (HCC) is a malignant tumor with hepatocellular differentiation and one of the most common cancers in the world.
This type of cancer is often diagnosed when the survival time is measured in months causing high death rates [1].
For the purpose of supporting histopathology diagnosis of HCC, we have developed an experimental system of “feature measurement software for liver biopsy” [2].
The system provides pathologists with the quantitative measurement of tissue morphology using a digital slide of hematoxylin-eosin (HE) stained liver tissue specimen, as well as the HCC detection based on those measurement results.
In this study, we are focusing on the classification process of HCC images in the system.
Previously, Kiyuna et al.
[3] had introduced an automatic classification of HCC images based on 13 types of nuclear and structural features, where each feature consists of 6 statistical distributions.
In order to improve the classification performance, we have developed methods to segment the liver tissue and quantify additional tissue features such as trabecular morphology [4].
This paper reports the evaluation results on the impact of the segmentation and the additional features in the HCC detection performance.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Abdul Aziz, Maulana& Kanazawa, Hiroshi& Murakami, Yuri& Kimura, Fumikazu& Yamaguchi, Masahiro& Kiyuna, Tomoharu…[et al.]. 2014. Enhancing Automatic Classification of Hepatocellular Carcinoma Images through Image Masking, Tissue Changes, and Trabecular Features. Analytical Cellular Pathology،Vol. 2014, no. 2014, pp.1-2.
https://search.emarefa.net/detail/BIM-1034184
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Abdul Aziz, Maulana…[et al.]. Enhancing Automatic Classification of Hepatocellular Carcinoma Images through Image Masking, Tissue Changes, and Trabecular Features. Analytical Cellular Pathology No. 2014 (2014), pp.1-2.
https://search.emarefa.net/detail/BIM-1034184
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Abdul Aziz, Maulana& Kanazawa, Hiroshi& Murakami, Yuri& Kimura, Fumikazu& Yamaguchi, Masahiro& Kiyuna, Tomoharu…[et al.]. Enhancing Automatic Classification of Hepatocellular Carcinoma Images through Image Masking, Tissue Changes, and Trabecular Features. Analytical Cellular Pathology. 2014. Vol. 2014, no. 2014, pp.1-2.
https://search.emarefa.net/detail/BIM-1034184
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1034184
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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