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基于3D医学图像的引流管分叉位置算法研究

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

作者信息

Pan Qiuling, Zhu Wei, Zhang Xiaolin, Chang Jincai, Cui Jianzhong

机构信息

College of Sciences, North China University of Science and Technology, Tangshan 063210, Hebei, China.

Department of Neurosurgery, Tangshan Gongren Hospital, Tangshan 063000, Hebei, China.

出版信息

Vis Comput Ind Biomed Art. 2020 Jan 14;3(1):2. doi: 10.1186/s42492-019-0039-0.

DOI:10.1186/s42492-019-0039-0
PMID:32240438
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7099540/
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.

摘要

基于患者的计算机断层扫描数据，我们使用阈值法分割出包含颅内血肿的区域，并重建了三维血肿模型。为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，并用于提取最佳外轴。根据多管引流管的特点和颅内血肿清除穿刺的临床需求，该算法可为血肿引流管提供最佳路径、穿刺点的精确位置及术前规划信息，对临床医生具有重要的指导意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/d4f12ebda2a4/42492_2019_39_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/d76ea9888330/42492_2019_39_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/efac2ce7ceab/42492_2019_39_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/4a588a9649d9/42492_2019_39_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/27ceaa6da4ab/42492_2019_39_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/ff8d671d3636/42492_2019_39_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/2cfec1d3cba1/42492_2019_39_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/28f23f0a207c/42492_2019_39_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/f0f3630c0855/42492_2019_39_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/d4f12ebda2a4/42492_2019_39_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/d76ea9888330/42492_2019_39_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/efac2ce7ceab/42492_2019_39_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/4a588a9649d9/42492_2019_39_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/27ceaa6da4ab/42492_2019_39_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/ff8d671d3636/42492_2019_39_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/2cfec1d3cba1/42492_2019_39_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/28f23f0a207c/42492_2019_39_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/f0f3630c0855/42492_2019_39_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7c5/7099540/d4f12ebda2a4/42492_2019_39_Fig9_HTML.jpg

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