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An Automatic Method for Renal Cortex Segmentation on CT Images. Evaluation on Kidney Donors

机译：CT图像上肾皮层分割的自动方法。 肾脏捐赠者的评价

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摘要

Rationale and Objectives: The aims of this study were to develop and validate an automated method to segment the renal cortex on contrast-enhanced abdominal computed tomographic images from kidney donors and to track cortex volume change after donation. Materials and Methods: A three-dimensional fully automated renal cortex segmentation method was developed and validated on 37 arterial phase computed tomographic data sets (27 patients, 10 of whom underwent two computed tomographic scans before and after nephrectomy) using leave-one-out strategy. Two expert interpreters manually segmented the cortex slice by slice, and linear regression analysis and Bland-Altman plots were used to compare automated and manual segmentation. The true-positive and false-positive volume fractions were also calculated to evaluate the accuracy of the proposed method. Cortex volume changes in 10 subjects were also calculated. Results: The linear regression analysis results showed that the automated and manual segmentation methods had strong correlations, with Pearson's correlations of 0.9529, 0.9309, 0.9283, and 0.9124 between intraobserver variation, interobserver variation, automated and user 1, and automated and user 2, respectively (P < .001 for all analyses). The Bland-Altman plots for cortex segmentation also showed that the automated and manual methods had agreeable segmentation. The mean volume increase of the cortex for the 10 subjects was 35.1 ± 13.2% (P < .01 by paired t test). The overall true-positive and false-positive volume fractions for cortex segmentation were 90.15 ± 3.11% and 0.85 ± 0.05%. With the proposed automated method, the time for cortex segmentation was reduced from 20 minutes for manual segmentation to 2 minutes. Conclusions: The proposed method was accurate and efficient and can replace the current subjective and time-consuming manual procedure. The computer measurement confirms the volume of renal cortex increases after kidney donation.
机译：理由和目标：本研究的目的是开发和验证自动化方法，以在肾脏捐赠者举行对比增强的腹部计算机断层图像上分段肾皮层，并在捐赠后跟踪皮质体积变化。材料和方法：在37个动脉期计算断层数据集（27名患者，其中10名肾切除术前后两次计算断层扫描）的37个动脉期计算和验证了三维全自动肾皮质分割方法。 。手动将两个专家解释器通过切片分割皮质切片，并使用线性回归分析和Bland-Altman图来比较自动化和手动分割。还计算了真正阳性和假阳性体积分数以评估所提出的方法的准确性。还计算了10个受试者的皮质体积变化。结果：线性回归分析结果表明，自动化和手动分割方法具有强烈的相关性，Pearson分别在0.9529,0.9309,0.9283和0.9124之间的相关性分别之间的0.9529,0.9309,0.9283和0.9124分别分别在内（所有分析的p <.001）。 Cortex分段的Bland-Altman图也表明，自动化和手动方法具有令人愉悦的分割。 10个受试者皮质的平均体积增加为35.1±13.2％（P <0.01通过配对T测试）。皮质分段的总体阳性和假阳性体积分数为90.15±3.11％和0.85±0.05％。利用所提出的自动化方法，将皮质分段的时间从20分钟减少到2分钟的手动分段。结论：提出的方法准确有效，可以取代目前的主观和耗时的手动程序。计算机测量确认肾脏捐赠后肾皮层的体积增加。

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  • 来源
    《Academic radiology》 |2012年第5期|共9页
  • 作者

    ChenX.; SummersR.M.; ChoM.; BagciU.; YaoJ.;

  • 作者单位

    Radiology and Imaging Sciences Department National Institutes of Health Clinical Center Building;

    Radiology and Imaging Sciences Department National Institutes of Health Clinical Center Building;

    Kidney Disease Branch National Institute of Diabetes and Digestive and Kidney Diseases Bethesda;

    Radiology and Imaging Sciences Department National Institutes of Health Clinical Center Building;

    Radiology and Imaging Sciences Department National Institutes of Health Clinical Center Building;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 放射医学;
  • 关键词

    Automatic renal cortex segmentation; Kidney; Kidney donors; Renal cortex;

    机译：自动肾皮层分割;肾脏;肾脏捐赠者;肾皮层;

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