A Sophisticated Convolutional Neural Network Model for Brain Tumor Classification

被引:0
|
作者
Balasooriya, Narmada M. [1 ]
Nawarathna, Ruwan D. [2 ]
机构
[1] Univ Peradeniya, Postgrad Inst Sci, Peradeniya 20400, Sri Lanka
[2] Univ Peradeniya, Dept Stat & Comp Sci, Peradeniya 20400, Sri Lanka
来源
2017 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS (ICIIS) | 2017年
关键词
MRI; Brain tumor; Convolutional Neural Networks; Cross Validation;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Magnetic Resonance Imaging(MRI) is one of the commonly used medical imaging modality that provides informative data for brain tumor diagnosis other than Computed Tomography(CT). A key challenge when a physician studies the MRI data is the time and effort he has to put in diagnosing the tumors. The objective of this research is to recognize the tumor type when a collection of MRI images of a patient is given. To achieve this goal, a deep learning algorithm is developed using Convolutional Neural Networks(CNNs). Nowadays, most of image classification problems use CNNs as they deliver higher precision and accuracy compared to other existing algorithms. Here, a sophisticated CNN model is developed, trained using cross validation and tested on brain MRI images obtained from open databases. The performance of the proposed model is promising.
引用
收藏
页码:180 / 184
页数:5
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