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Grade identification of astrocytoma using image processing — A literature review

机译:利用图像处理技术鉴定星形细胞瘤的等级-文献综述

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Brain tumor grade identification is an invasive technique and clinicians rely on biopsy. Tumor grade (low/high) identification can be done on astrocytoma (brain tumor) using MRI, a non-invasive technique. Image segmentation, de-noising and feature extraction are the various techniques which are refined for segmenting the astrocytoma region using MRI images. Grey Level Co-occurrence Matrix (GLCM) is used for extracting the texture features from segmented tumor region. These features are then correlated with already saved features in the database. After that various classifiers are used to classify the MR images into (Low/High) grade Astrocytoma. The submitted approach of grade identification is estimated on the basis of various values such as severity, specificity and accuracy.
机译:脑肿瘤等级鉴定是一种侵入性技术,临床医生依靠活检。可以使用非侵入性技术MRI对星形细胞瘤(脑肿瘤)进行肿瘤等级(低/高)鉴定。图像分割,去噪和特征提取是使用MRI图像对星形细胞瘤区域进行细分的各种技术。灰度共生矩阵(GLCM)用于从分割的肿瘤区域中提取纹理特征。然后将这些功能与数据库中已保存的功能相关联。之后,使用各种分类器将MR图像分类为(低/高)等级星形细胞瘤。根据各种值(例如严重性,特异性和准确性)估算提交的等级识别方法。

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