基于GVF Snake的脑CT图像颅内出血性中风分割

Muhamad Rudiansyah, T. A. Sardjono, R. Mardiyanto
{"title":"基于GVF Snake的脑CT图像颅内出血性中风分割","authors":"Muhamad Rudiansyah, T. A. Sardjono, R. Mardiyanto","doi":"10.1109/ISITIA.2018.8711155","DOIUrl":null,"url":null,"abstract":"Segmentation of Intracerebral Hemorrhagic Strokes from Brain CT Image is a process of segmenting homogenous area to measure its volume. The purpose of this paper is to calculated the ROI area from ICH bleeding, the results then are compared with the results of CT Scan area. The process used DICOM image with Gradient Vector Flow (GVF) Snake method. DICOM image shows the pixel area; therefore, by calculating the resulted area from the segmentation, the homogenous area or the bleeding area of intracerebral hemorrhagic (ICH) ca be determined. GVF Snake method is a type of active contours that can be used for bleeding segmentation. The formulated constants for image are σ=5, µ=0.1, GVF Iteration=40, α=0.05, ß=0, y=5, k=5, and Snake Iteration = 40. The result of ROI GVF Snake area is compared with ROI area from the CT-Scan, with the similarity of 79.937%.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"4311 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Segmentation of the Intracerebral Hemorrhagic Strokes (Bleeds) from Brain CT Image Based on GVF Snake\",\"authors\":\"Muhamad Rudiansyah, T. A. Sardjono, R. Mardiyanto\",\"doi\":\"10.1109/ISITIA.2018.8711155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Segmentation of Intracerebral Hemorrhagic Strokes from Brain CT Image is a process of segmenting homogenous area to measure its volume. The purpose of this paper is to calculated the ROI area from ICH bleeding, the results then are compared with the results of CT Scan area. The process used DICOM image with Gradient Vector Flow (GVF) Snake method. DICOM image shows the pixel area; therefore, by calculating the resulted area from the segmentation, the homogenous area or the bleeding area of intracerebral hemorrhagic (ICH) ca be determined. GVF Snake method is a type of active contours that can be used for bleeding segmentation. The formulated constants for image are σ=5, µ=0.1, GVF Iteration=40, α=0.05, ß=0, y=5, k=5, and Snake Iteration = 40. The result of ROI GVF Snake area is compared with ROI area from the CT-Scan, with the similarity of 79.937%.\",\"PeriodicalId\":388463,\"journal\":{\"name\":\"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)\",\"volume\":\"4311 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISITIA.2018.8711155\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISITIA.2018.8711155","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

颅内出血性中风的CT图像分割是对均匀区域进行分割以测量其体积的过程。本文的目的是计算颅内出血的ROI面积,并将结果与CT扫描面积进行比较。该过程采用DICOM图像与梯度矢量流(GVF) Snake方法。DICOM图像显示像素区域;因此,通过计算分割的结果面积,可以确定颅内出血(ICH)的均匀区或出血区。GVF Snake方法是一种可用于出血分割的活动轮廓。图像的公式常数为σ=5,µ=0.1,GVF Iteration=40, α=0.05, ß=0, y=5, k=5, Snake Iteration=40。将感兴趣的GVF Snake区域与ct扫描的感兴趣区域进行比较,相似度为79.937%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Segmentation of the Intracerebral Hemorrhagic Strokes (Bleeds) from Brain CT Image Based on GVF Snake
Segmentation of Intracerebral Hemorrhagic Strokes from Brain CT Image is a process of segmenting homogenous area to measure its volume. The purpose of this paper is to calculated the ROI area from ICH bleeding, the results then are compared with the results of CT Scan area. The process used DICOM image with Gradient Vector Flow (GVF) Snake method. DICOM image shows the pixel area; therefore, by calculating the resulted area from the segmentation, the homogenous area or the bleeding area of intracerebral hemorrhagic (ICH) ca be determined. GVF Snake method is a type of active contours that can be used for bleeding segmentation. The formulated constants for image are σ=5, µ=0.1, GVF Iteration=40, α=0.05, ß=0, y=5, k=5, and Snake Iteration = 40. The result of ROI GVF Snake area is compared with ROI area from the CT-Scan, with the similarity of 79.937%.
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
期刊最新文献
Losing Synchronism Technique based on Critical Trajectory Method for Obtaining the CCT with Installing SCES Design of a SINRD bandpass filter based on equivalent circuit method A Geometry-Based Underwater Acoustic Channel Model for Time Reversal Acoustic Communication Implementation and Feasibility Analysis of GSM Based Smart Energy Meter for Digitalized Power Consumption with Advanced Features Performance of BLDC Motor Speed Control Based on Hysteresis Current Control Mechanism
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1