Differentiating Grade in Breast Invasive Ductal Carcinoma Using Texture Analysis of MRI
المؤلفون المشاركون
Yuan, Gaoteng
Liu, Yihui
Huang, Wei
Hu, Bing
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-04-07
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Purpose.
The objective of this study is to investigate the use of texture analysis (TA) of magnetic resonance image (MRI) enhanced scan and machine learning methods for distinguishing different grades in breast invasive ductal carcinoma (IDC).
Preoperative prediction of the grade of IDC can provide reference for different clinical treatments, so it has important practice values in clinic.
Methods.
Firstly, a breast cancer segmentation model based on discrete wavelet transform (DWT) and K-means algorithm is proposed.
Secondly, TA was performed and the Gabor wavelet analysis is used to extract the texture feature of an MRI tumor.
Then, according to the distance relationship between the features, key features are sorted and feature subsets are selected.
Finally, the feature subset is classified by using a support vector machine and adjusted parameters to achieve the best classification effect.
Results.
By selecting key features for classification prediction, the classification accuracy of the classification model can reach 81.33%.
3-, 4-, and 5-fold cross-validation of the prediction accuracy of the support vector machine model is 77.79%~81.94%.
Conclusion.
The pathological grading of IDC can be predicted and evaluated by texture analysis and feature extraction of breast tumors.
This method can provide much valuable information for doctors’ clinical diagnosis.
With further development, the model demonstrates high potential for practical clinical use.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yuan, Gaoteng& Liu, Yihui& Huang, Wei& Hu, Bing. 2020. Differentiating Grade in Breast Invasive Ductal Carcinoma Using Texture Analysis of MRI. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1139538
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yuan, Gaoteng…[et al.]. Differentiating Grade in Breast Invasive Ductal Carcinoma Using Texture Analysis of MRI. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1139538
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yuan, Gaoteng& Liu, Yihui& Huang, Wei& Hu, Bing. Differentiating Grade in Breast Invasive Ductal Carcinoma Using Texture Analysis of MRI. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1139538
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1139538
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