BRAIN TUMOR CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK ON MRI IMAGES

Shubhangi S. Veer, P. Patil
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引用次数: 13

Abstract

In this paper, an attempt has been made to summarize the multi-resolution transformation and the different classifiers useful to analyze the brain tumor using MRI. X-ray, MRI, Ultrasound etc. are different techniques used to scan brain tumor images. Radiologist prefers MRI to get detail information about tumor to help him diagnoses. In this paper we have used MRI of brain tumor for analysis. We have used Digital image processing tool for detection of the tumor. The identification, detection and classification of brain tumor have been done by extracting features from MRI with the help of wavelet transformation. The MRI of brain tumor is classified into two categories normal and abnormal brain. In this work Digital image processing has been used as a tool for getting clear and exact details about tumor in earlier stages. This helps the physicians and practitioners for diagnoses. Key word – Brain tumor, Wavelet transform, segmentation.
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基于mri图像的人工神经网络脑肿瘤分类
本文尝试对MRI对脑肿瘤的多分辨率变换和不同的分类器进行综述。x光、核磁共振、超声等是扫描脑肿瘤图像的不同技术。放射科医生更喜欢用核磁共振成像来获得肿瘤的详细信息,以帮助他进行诊断。本文采用脑肿瘤MRI进行分析。我们使用数字图像处理工具对肿瘤进行检测。利用小波变换对MRI图像进行特征提取,实现了脑肿瘤的识别、检测和分类。脑肿瘤的MRI分为正常脑和异常脑两类。在这项工作中,数字图像处理已被用作获得肿瘤早期清晰和准确细节的工具。这有助于医生和从业人员的诊断。关键词:脑肿瘤,小波变换,分割。
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