Texture analysis applied to brain MRI to classify low and high grade gliomas

被引：0

作者：

Suarez Garcia, Jose Gerardo ^{[1
]}

Hernandez Lopez, Javier Miguel ^{[1
]}

Moreno Barbosa, Eduardo ^{[1
]}

Martinez Hernandez, Mario Ivan ^{[1
]}

Tejeda Munoz, Guillermo ^{[1
]}

de Celis Alonso, Benito ^{[1
]}

机构：

[1] BUAP, Fac Phys & Math, Puebla, Mexico

来源：

XV MEXICAN SYMPOSIUM ON MEDICAL PHYSICS | 2019年 / 2090卷

关键词：

CLASSIFICATION; FEATURES;

D O I：

10.1063/1.5095912

中图分类号：

Q6 [生物物理学];

学科分类号：

071011 ;

摘要：

Gliomas can be classified as either low grade glioma (LGG) or high grade glioma (HGG). Standard diagnosis is based on histopathological tests obtained from a surgical resection or a stereotactic biopsy. Due to their heterogeneity, these tumors can be misclassified. Therefore, there is a need to develop non-invasive and automatic methods that could help specialists with their correct classification. The aim of this work was to develop a computational classification method which distinguished LGGs from HGGs, based on texture analysis of magnetic resonance images (MRI). The model reported was based on a simple methodology and proved to be useful for the classification of gliomas.

引用

页数：6

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[11] Serial stereotactic biopsy of brainstem lesions in adults improves diagnostic accuracy compared with MRI only [J].