Research on a bifurcation location algorithm of a drainage tube based on 3D medical images.

4区 计算机科学 Q1 Arts and Humanities Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-01-14 DOI:10.1186/s42492-019-0039-0
Qiuling Pan, Wei Zhu, Xiaolin Zhang, Jincai Chang, Jianzhong Cui
{"title":"Research on a bifurcation location algorithm of a drainage tube based on 3D medical images.","authors":"Qiuling Pan,&nbsp;Wei Zhu,&nbsp;Xiaolin Zhang,&nbsp;Jincai Chang,&nbsp;Jianzhong Cui","doi":"10.1186/s42492-019-0039-0","DOIUrl":null,"url":null,"abstract":"<p><p>Based on patient computerized tomography data, we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model. To improve the efficiency and accuracy of identifying puncture points, a point-cloud search arithmetic method for modified adaptive weighted particle swarm optimization is proposed and used for optimal external axis extraction. According to the characteristics of the multitube drainage tube and the clinical needs of puncture for intracranial hematoma removal, the proposed algorithm can provide an optimal route for a drainage tube for the hematoma, the precise position of the puncture point, and preoperative planning information, which have considerable instructional significance for clinicians.</p>","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"3 1","pages":"2"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s42492-019-0039-0","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Visual Computing for Industry, Biomedicine, and Art","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1186/s42492-019-0039-0","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Arts and Humanities","Score":null,"Total":0}
引用次数: 4

Abstract

Based on patient computerized tomography data, we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model. To improve the efficiency and accuracy of identifying puncture points, a point-cloud search arithmetic method for modified adaptive weighted particle swarm optimization is proposed and used for optimal external axis extraction. According to the characteristics of the multitube drainage tube and the clinical needs of puncture for intracranial hematoma removal, the proposed algorithm can provide an optimal route for a drainage tube for the hematoma, the precise position of the puncture point, and preoperative planning information, which have considerable instructional significance for clinicians.

Abstract Image

Abstract Image

Abstract Image

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
基于三维医学图像的引流管分岔定位算法研究。
基于患者计算机断层数据,采用阈值法分割颅内血肿区域,重建血肿三维模型。为了提高穿刺点识别的效率和准确性,提出了一种改进的自适应加权粒子群优化的点云搜索算法,并将其用于最优外轴提取。根据多管引流管的特点和颅内血肿清除穿刺的临床需要,提出的算法可以提供血肿引流管的最优路径、穿刺点的精确位置以及术前规划信息,对临床医生具有相当的指导意义。
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 去求助
来源期刊
Visual Computing for Industry, Biomedicine, and Art
Visual Computing for Industry, Biomedicine, and Art Arts and Humanities-Visual Arts and Performing Arts
CiteScore
5.60
自引率
0.00%
发文量
28
审稿时长
5 weeks
期刊最新文献
Discrimination between leucine-rich glioma-inactivated 1 antibody encephalitis and gamma-aminobutyric acid B receptor antibody encephalitis based on ResNet18. Hyperparameter optimization for cardiovascular disease data-driven prognostic system. Survey of methods and principles in three-dimensional reconstruction from two-dimensional medical images. Vision transformer architecture and applications in digital health: a tutorial and survey. DB-DCAFN: dual-branch deformable cross-attention fusion network for bacterial segmentation.
×
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