分割头部ct扫描计算脑出血体积百分比

Rizal Romadhoni Hidayatullah, R. Sigit, Sigit Wasista
{"title":"分割头部ct扫描计算脑出血体积百分比","authors":"Rizal Romadhoni Hidayatullah, R. Sigit, Sigit Wasista","doi":"10.1109/KCIC.2017.8228603","DOIUrl":null,"url":null,"abstract":"Brain hemorrhage is a serious category of head injury that can have a fatal impact on brain function and performance. But sometimes the identification of cerebral hemorrhage can not be known immediately. So far, the identification of cerebral hemorrhage is done through CT Scan image observation that requires special skills. Therefore we need a certain method that can segment the CT Scan image quickly and automated. The goal is to obtain the image segmentation of brain bleeding more quickly and accurately. So patients with cerebral hemorrhage can immediately obtain medical treatment in accordance with the needs. The preprocessing process of CT Scan image starts from the preprocessing phase of the CT Scan image using color filtering, erosion and dilation methods. This stage is done to clarify the cerebral hemorrhage and eliminate the noise contained in the image. Then performed watershed and cropping segmentation to separate the skull bones of the skull with brain tissue. The next step is to improve the image quality using median filtering. Then the image is again segmented using the threshold method to separate the image of cerebral hemorrhage as the observed object. Last performed the calculation of area and volume percentage of bleeding in the brain. From the system test obtained the calculation of brain area has an average error of 1.13%. As for the test calculation of the area of bleeding has an average error of 11.17%.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Segmentation of head CT-scan to calculate percentage of brain hemorrhage volume\",\"authors\":\"Rizal Romadhoni Hidayatullah, R. Sigit, Sigit Wasista\",\"doi\":\"10.1109/KCIC.2017.8228603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Brain hemorrhage is a serious category of head injury that can have a fatal impact on brain function and performance. But sometimes the identification of cerebral hemorrhage can not be known immediately. So far, the identification of cerebral hemorrhage is done through CT Scan image observation that requires special skills. Therefore we need a certain method that can segment the CT Scan image quickly and automated. The goal is to obtain the image segmentation of brain bleeding more quickly and accurately. So patients with cerebral hemorrhage can immediately obtain medical treatment in accordance with the needs. The preprocessing process of CT Scan image starts from the preprocessing phase of the CT Scan image using color filtering, erosion and dilation methods. This stage is done to clarify the cerebral hemorrhage and eliminate the noise contained in the image. Then performed watershed and cropping segmentation to separate the skull bones of the skull with brain tissue. The next step is to improve the image quality using median filtering. Then the image is again segmented using the threshold method to separate the image of cerebral hemorrhage as the observed object. Last performed the calculation of area and volume percentage of bleeding in the brain. From the system test obtained the calculation of brain area has an average error of 1.13%. As for the test calculation of the area of bleeding has an average error of 11.17%.\",\"PeriodicalId\":117148,\"journal\":{\"name\":\"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KCIC.2017.8228603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KCIC.2017.8228603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

脑出血是一种严重的头部损伤,可对大脑功能和表现产生致命影响。但有时脑出血的鉴定不能立即知道。目前,脑出血的诊断主要是通过CT扫描图像观察来完成的,这需要特殊的技能。因此,我们需要一种能够快速、自动化地分割CT扫描图像的方法。目的是为了更快、更准确地获得脑出血的图像分割。因此脑出血患者可以根据需要立即就医。CT扫描图像的预处理过程从CT扫描图像的预处理阶段开始,采用彩色滤波、侵蚀、膨胀等方法。这一阶段是为了澄清脑出血,消除图像中包含的噪声。然后进行分水岭分割和裁剪分割,将颅骨与脑组织分离。下一步是使用中值滤波来提高图像质量。然后再用阈值法对图像进行分割,分离出脑出血图像作为观察对象。最后计算脑出血面积和体积百分比。从系统测试得到的脑面积计算平均误差为1.13%。出血面积的试验计算平均误差为11.17%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Segmentation of head CT-scan to calculate percentage of brain hemorrhage volume
Brain hemorrhage is a serious category of head injury that can have a fatal impact on brain function and performance. But sometimes the identification of cerebral hemorrhage can not be known immediately. So far, the identification of cerebral hemorrhage is done through CT Scan image observation that requires special skills. Therefore we need a certain method that can segment the CT Scan image quickly and automated. The goal is to obtain the image segmentation of brain bleeding more quickly and accurately. So patients with cerebral hemorrhage can immediately obtain medical treatment in accordance with the needs. The preprocessing process of CT Scan image starts from the preprocessing phase of the CT Scan image using color filtering, erosion and dilation methods. This stage is done to clarify the cerebral hemorrhage and eliminate the noise contained in the image. Then performed watershed and cropping segmentation to separate the skull bones of the skull with brain tissue. The next step is to improve the image quality using median filtering. Then the image is again segmented using the threshold method to separate the image of cerebral hemorrhage as the observed object. Last performed the calculation of area and volume percentage of bleeding in the brain. From the system test obtained the calculation of brain area has an average error of 1.13%. As for the test calculation of the area of bleeding has an average error of 11.17%.
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:481959085
Book学术官方微信