A Novel Multiinstance Learning Approach for Liver Cancer Recognition on Abdominal CT Images Based on CPSO-SVM and IO
المؤلفون المشاركون
Yi, Dehui
Zheng, Ruiping
Zhao, Di
Jiang, Huiyan
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-12-04
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
A novel multi-instance learning (MIL) method is proposed to recognize liver cancer with abdominal CT images based on instance optimization (IO) and support vector machine with parameters optimized by a combination algorithm of particle swarm optimization and local optimization (CPSO-SVM).
Introducing MIL into liver cancer recognition can solve the problem of multiple regions of interest classification.
The images we use in the experiments are liver CT images extracted from abdominal CT images.
The proposed method consists of two main steps: (1) obtaining the key instances through IO by texture features and a classification threshold in classification of instances with CPSO-SVM and (2) predicting unknown samples with the key instances and the classification threshold.
By extracting the instances equally based on the entire image, the proposed method can ignore the procedure of tumor region segmentation and lower the demand of segmentation accuracy of liver region.
The normal SVM method and two MIL algorithms, Citation-kNN algorithm and WEMISVM algorithm, have been chosen as comparing algorithms.
The experimental results show that the proposed method can effectively recognize liver cancer images from two kinds of cancer CT images and greatly improve the recognition accuracy.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jiang, Huiyan& Zheng, Ruiping& Yi, Dehui& Zhao, Di. 2013. A Novel Multiinstance Learning Approach for Liver Cancer Recognition on Abdominal CT Images Based on CPSO-SVM and IO. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-471976
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jiang, Huiyan…[et al.]. A Novel Multiinstance Learning Approach for Liver Cancer Recognition on Abdominal CT Images Based on CPSO-SVM and IO. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-471976
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jiang, Huiyan& Zheng, Ruiping& Yi, Dehui& Zhao, Di. A Novel Multiinstance Learning Approach for Liver Cancer Recognition on Abdominal CT Images Based on CPSO-SVM and IO. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-471976
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-471976
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