Classification of Tumors in Breast Echography using a SVM algorithm

被引：11

作者：

Acevedo-Contla, Pedro ^{[1
]}

Vazquez-Hernandez, Monica ^{[1
]}

机构：

[1] Univ Nacl Autonoma Mexico, Inst Invest Matemat Aplicadas & Sistemas, Mexico City, DF, Mexico

来源：

2019 6TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2019) | 2019年

关键词：

echography; ultrasound; tumor classfication;

D O I：

10.1109/CSCI49370.2019.00128

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work tumor classWcation was performed using K-means and GLCM algorithms to segment ultrasound images. In order to apply Stavros criteria, a lineal support vector machine (SVM) algorithm was used to classify benign and malignant tumors. 94% of echographies were correctly classified.

引用

页码：686 / 689

页数：4

共 8 条

[1] Automated breast cancer detection and classification using ultrasound images: A survey [J].