{"title":"从脑磁共振图像中检测脑肿瘤及肿瘤内结构","authors":"Mukesh M Goswami, B. Rao","doi":"10.1109/ICICICT54557.2022.9917845","DOIUrl":null,"url":null,"abstract":"Discovering the brain tumor and Intra-Tumoral structures from the brain tumor MR images is an essential task in tumor diagnostics. An automated system that accurately detects the brain tumor and intra-Tumoral structure from MR images will help the patients with a speedy recovery. It also reduces the time required for diagnosis.Detection of the brain tumor and the intra-Tumoral region is an intricate task as the structure of the tumor has different size, shape, location, and variation in intensity range. Here we have analyzed a variety of supervised and unsupervised learning techniques for the uncovering of a brain tumor and intraTumoral structures. We have designed a multistage hybrid approach using the information from different MR models such as features from individual images and features from the fused images to improve the accuracy of detecting a brain tumor and internal tumor structure from MRI images.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detection of Brain Tumor & Intra-Tumoral Structures from the Brain MR Images\",\"authors\":\"Mukesh M Goswami, B. Rao\",\"doi\":\"10.1109/ICICICT54557.2022.9917845\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Discovering the brain tumor and Intra-Tumoral structures from the brain tumor MR images is an essential task in tumor diagnostics. An automated system that accurately detects the brain tumor and intra-Tumoral structure from MR images will help the patients with a speedy recovery. It also reduces the time required for diagnosis.Detection of the brain tumor and the intra-Tumoral region is an intricate task as the structure of the tumor has different size, shape, location, and variation in intensity range. Here we have analyzed a variety of supervised and unsupervised learning techniques for the uncovering of a brain tumor and intraTumoral structures. We have designed a multistage hybrid approach using the information from different MR models such as features from individual images and features from the fused images to improve the accuracy of detecting a brain tumor and internal tumor structure from MRI images.\",\"PeriodicalId\":246214,\"journal\":{\"name\":\"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICICT54557.2022.9917845\",\"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 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICICT54557.2022.9917845","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of Brain Tumor & Intra-Tumoral Structures from the Brain MR Images
Discovering the brain tumor and Intra-Tumoral structures from the brain tumor MR images is an essential task in tumor diagnostics. An automated system that accurately detects the brain tumor and intra-Tumoral structure from MR images will help the patients with a speedy recovery. It also reduces the time required for diagnosis.Detection of the brain tumor and the intra-Tumoral region is an intricate task as the structure of the tumor has different size, shape, location, and variation in intensity range. Here we have analyzed a variety of supervised and unsupervised learning techniques for the uncovering of a brain tumor and intraTumoral structures. We have designed a multistage hybrid approach using the information from different MR models such as features from individual images and features from the fused images to improve the accuracy of detecting a brain tumor and internal tumor structure from MRI images.