利用Glcm分析脑肿瘤MRI图像纹理特征的有效方法

A. Kukreja, A. Wadhwani, S. Wadhwani
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引用次数: 0

摘要

肿瘤的发现和消除是医学科学中仍然存在的一个问题。CT和MRI成像技术有助于专科医生获得较好的感知,但由于肿瘤组织的高度变异性,对不同患者的处理过程带来了费力的风险。本文采用GLCM对肿瘤图像进行预处理、分割和特征提取三个阶段的处理。加入源MRI图像后,先将原始图像转换为灰度图像进行预处理,然后使用滤波器去除噪声,使用算术算子进行增强,然后进行阈值分割和分水岭分割阶段,再进行形态学运算检测肿瘤,最后利用灰度共生矩阵进行纹理分析。上述建议的程序和技术适用于在较短的时间内完成报告。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Way to Analysis the Texural Features of Brain Tumor MRI Image Using Glcm
Tumor spotting and elimination is one problematic issue in medical science that still remains. Untimely imaging techniques CT and MRI imaging techniques aid specialist in coming up with preferable perception, but because of high variability in tumor tissue of divergent patient process come up with laborious risks .In this paper, tumor image processing concern the three stages, namely pre-processing, segmentation and feature extraction using GLCM. After the accession of the source MRI image, it is preprocessed by converting the original image to grayscale image, then use of filters for removal of noise and using arithmetic operators for enhancement, then the stage of thresholding segmentation and watershed segmentation is done followed by a morphological operation to detection of tumor, thereby texture analysis using Gray Level Co -Occurrence Matrix. The above proposed procedures and techniques is applicable in accomplishing the reports axiomatically in less span of time.
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