{"title":"一种有效的磁共振脑图像肿瘤分割的可能性模糊聚类方法","authors":"B. Saravanan, M. Duraipandian, V. Pandiaraj","doi":"10.1109/I-SMAC55078.2022.9987388","DOIUrl":null,"url":null,"abstract":"The segmentation of tumors in magnetic resonance imaging (MRI) is a medical emergency operation. Weakened MR images of the brain are used to segment them using the fuzzy C-means (FCM) clustering technique. The run time is longer because of the need to continuously calculate the clustering parameters. Using the probabilistic fuzzy clustering (PFC) technique for brain MRI image segmentation is recommended by the authors of this article. Morphological reconstruction and computation of local spatial similarity factors are performed before commencing the clustering step. Integrating a local spatial similarity factor into the morphological reconstruction process reduces noise, while maintaining the information's structural integrity.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Effective Possibilistic Fuzzy Clustering Method for Tumor Segmentation in MRI brain Images\",\"authors\":\"B. Saravanan, M. Duraipandian, V. Pandiaraj\",\"doi\":\"10.1109/I-SMAC55078.2022.9987388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The segmentation of tumors in magnetic resonance imaging (MRI) is a medical emergency operation. Weakened MR images of the brain are used to segment them using the fuzzy C-means (FCM) clustering technique. The run time is longer because of the need to continuously calculate the clustering parameters. Using the probabilistic fuzzy clustering (PFC) technique for brain MRI image segmentation is recommended by the authors of this article. Morphological reconstruction and computation of local spatial similarity factors are performed before commencing the clustering step. Integrating a local spatial similarity factor into the morphological reconstruction process reduces noise, while maintaining the information's structural integrity.\",\"PeriodicalId\":306129,\"journal\":{\"name\":\"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I-SMAC55078.2022.9987388\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SMAC55078.2022.9987388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Effective Possibilistic Fuzzy Clustering Method for Tumor Segmentation in MRI brain Images
The segmentation of tumors in magnetic resonance imaging (MRI) is a medical emergency operation. Weakened MR images of the brain are used to segment them using the fuzzy C-means (FCM) clustering technique. The run time is longer because of the need to continuously calculate the clustering parameters. Using the probabilistic fuzzy clustering (PFC) technique for brain MRI image segmentation is recommended by the authors of this article. Morphological reconstruction and computation of local spatial similarity factors are performed before commencing the clustering step. Integrating a local spatial similarity factor into the morphological reconstruction process reduces noise, while maintaining the information's structural integrity.