Multistage approach for automatic spleen segmentation in MRI sequences

Antonia Mihaylova, V. Georgieva, P. Petrov
{"title":"Multistage approach for automatic spleen segmentation in MRI sequences","authors":"Antonia Mihaylova, V. Georgieva, P. Petrov","doi":"10.1504/ijris.2020.10028339","DOIUrl":null,"url":null,"abstract":"Most of the known methods of segmentation of the abdominal organs are not automated for the whole series of images or are semi-automatic and require additional intervention by the user. This is typical for cases where the difference in intensity of the grey level between the subject and the background is small. This paper presents a multistage approach for spleen segmentation from MRI-sequences. It is based on segmentation methods such as active contours without edges and k-mean clustering. The proposed approach consists of some basic stages. The first stage is pre-processing, based on image enhancement and morphological operation. Two atlas models are created, which are used in the initial image to define the initial contour at which the segmentation begins. The proposed approach allows extracting the spleen in the different depth images, which has a variable form and unstable position. The conducted experiments are showing the robustness of the proposed approach. The obtained results demonstrate the effectiveness of the approach for application in screening diagnostics.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Reason. based Intell. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijris.2020.10028339","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Most of the known methods of segmentation of the abdominal organs are not automated for the whole series of images or are semi-automatic and require additional intervention by the user. This is typical for cases where the difference in intensity of the grey level between the subject and the background is small. This paper presents a multistage approach for spleen segmentation from MRI-sequences. It is based on segmentation methods such as active contours without edges and k-mean clustering. The proposed approach consists of some basic stages. The first stage is pre-processing, based on image enhancement and morphological operation. Two atlas models are created, which are used in the initial image to define the initial contour at which the segmentation begins. The proposed approach allows extracting the spleen in the different depth images, which has a variable form and unstable position. The conducted experiments are showing the robustness of the proposed approach. The obtained results demonstrate the effectiveness of the approach for application in screening diagnostics.
MRI序列脾脏自动分割的多阶段方法
大多数已知的腹部器官分割方法都不是针对整个图像系列的自动化方法,或者是半自动的,需要用户的额外干预。这是典型的情况下,在灰度等级之间的差异的主题和背景是小的。本文提出了一种基于mri序列的多阶段脾脏分割方法。它基于无边缘活动轮廓和k-均值聚类等分割方法。提出的方法包括一些基本阶段。第一阶段是基于图像增强和形态学运算的预处理。创建两个地图集模型,用于初始图像中定义分割开始处的初始轮廓。该方法允许在不同深度的图像中提取脾脏,脾脏具有可变的形状和不稳定的位置。实验结果表明了该方法的鲁棒性。所得结果表明,该方法在筛选诊断中的应用是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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