{"title":"利用Glcm分析脑肿瘤MRI图像纹理特征的有效方法","authors":"A. Kukreja, A. Wadhwani, S. Wadhwani","doi":"10.38124/ijisrt20jul603","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":355617,"journal":{"name":"International Journal of Innovative Science and Research Technology","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient Way to Analysis the Texural Features of Brain Tumor MRI Image Using Glcm\",\"authors\":\"A. Kukreja, A. Wadhwani, S. Wadhwani\",\"doi\":\"10.38124/ijisrt20jul603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":355617,\"journal\":{\"name\":\"International Journal of Innovative Science and Research Technology\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovative Science and Research Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.38124/ijisrt20jul603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovative Science and Research Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.38124/ijisrt20jul603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.