从脑磁共振图像中检测脑肿瘤及肿瘤内结构

Mukesh M Goswami, B. Rao
{"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}
引用次数: 0

摘要

从脑肿瘤磁共振图像中发现肿瘤及肿瘤内结构是肿瘤诊断的一项重要任务。从磁共振图像中准确检测脑肿瘤和肿瘤内结构的自动化系统将帮助患者快速康复。它还减少了诊断所需的时间。脑肿瘤及其肿瘤内区域的检测是一项复杂的任务,因为肿瘤的结构具有不同的大小、形状、位置和强度范围的变化。在这里,我们分析了各种用于发现脑肿瘤和肿瘤内结构的监督和非监督学习技术。我们设计了一种多阶段混合方法,利用来自不同磁共振模型的信息,如来自单个图像的特征和来自融合图像的特征,以提高从MRI图像中检测脑肿瘤和内部肿瘤结构的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信