Head and Neck Cancer Tumor Segmentation Using Support Vector Machine in Dynamic Contrast-Enhanced MRI
المؤلفون المشاركون
Chen, Hanwei
Dan, Guo
Deng, Wei
Lin, Xiaoyi
Fang, Tianqi
Liu, Dexiang
Luo, Liangping
المصدر
Contrast Media & Molecular Imaging
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-5، 5ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-09-07
دولة النشر
مصر
عدد الصفحات
5
التخصصات الرئيسية
الملخص EN
Objective.
We aimed to propose an automatic method based on Support Vector Machine (SVM) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to segment the tumor lesions of head and neck cancer (HNC).
Materials and Methods.
120 DCE-MRI samples were collected.
Five curve features and two principal components of the normalized time-intensity curve (TIC) in 80 samples were calculated as the dataset in training three SVM classifiers.
The other 40 samples were used as the testing dataset.
The area overlap measure (AOM) and the corresponding ratio (CR) and percent match (PM) were calculated to evaluate the segmentation performance.
The training and testing procedure was repeated for 10 times, and the average performance was calculated and compared with similar studies.
Results.
Our method has achieved higher accuracy compared to the previous results in literature in HNC segmentation.
The average AOM with the testing dataset was 0.76 ± 0.08, and the mean CR and PM were 79 ± 9% and 86 ± 8%, respectively.
Conclusion.
With improved segmentation performance, our proposed method is of potential in clinical practice for HNC.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Deng, Wei& Luo, Liangping& Lin, Xiaoyi& Fang, Tianqi& Liu, Dexiang& Dan, Guo…[et al.]. 2017. Head and Neck Cancer Tumor Segmentation Using Support Vector Machine in Dynamic Contrast-Enhanced MRI. Contrast Media & Molecular Imaging،Vol. 2017, no. 2017, pp.1-5.
https://search.emarefa.net/detail/BIM-1141863
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Deng, Wei…[et al.]. Head and Neck Cancer Tumor Segmentation Using Support Vector Machine in Dynamic Contrast-Enhanced MRI. Contrast Media & Molecular Imaging No. 2017 (2017), pp.1-5.
https://search.emarefa.net/detail/BIM-1141863
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Deng, Wei& Luo, Liangping& Lin, Xiaoyi& Fang, Tianqi& Liu, Dexiang& Dan, Guo…[et al.]. Head and Neck Cancer Tumor Segmentation Using Support Vector Machine in Dynamic Contrast-Enhanced MRI. Contrast Media & Molecular Imaging. 2017. Vol. 2017, no. 2017, pp.1-5.
https://search.emarefa.net/detail/BIM-1141863
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1141863
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