Classification Of MRI Brain Tumor and Mammogram Images Using Learning Vector Quantization Neural Network

被引：0

作者：

Sonavane, Ravindra ^{[1
]}

Sonar, Poonam ^{[1
]}

Sutar, Surendra ^{[1
]}

机构：

[1] Rajiv Gandhi Inst Technol, Dept Elect & Telecommun, Bombay, Maharashtra, India

来源：

2017 IEEE 3RD INTERNATIONAL CONFERENCE ON SENSING, SIGNAL PROCESSING AND SECURITY (ICSSS) | 2017年

关键词：

ADF; Brain MRI; DDSM database; GLCM; LVQ; tumor;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A proper and accurate classification technique with detection of brain tumor has been presented and proposed. The system uses neural network based approach for brain and breast image classification. Now a day's Magnetic resonance imaging (MRI technique is used for early detection of any abnormal changes in tissues and organs. The projected method is evaluated on two distinct databases i.e. Clinical database is database of brain MRI and one more Standard Digital Database for Screening Mammography (DDSM). The proposed system consists of Preprocessing using image normalization, morphological operations using erosion, dilation and Anisotropic Diffusion Filter (ADF), Extraction of texture feature using gray level co-occurrence matrix (GLCM) and classification into normal and abnormal using machine learning algorithm and quantization techniques i.e. LVQ. The proposed system achieved the accuracy of 68.85% for DDSM mammography database and 79.35% on clinical brain MRI database

引用

页码：301 / 307

页数：7

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