...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computers in Biology and Medicine >3D segmentation of exterior wall surface of abdominal aortic aneurysm from CT images using variable neighborhood search
【24h】

3D segmentation of exterior wall surface of abdominal aortic aneurysm from CT images using variable neighborhood search

机译：使用可变邻域搜索CT图像的腹主动脉瘤外壁表面的3D分割

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A 3D model of abdominal aortic aneurysm (AAA) can provide useful anatomical information for clinical management and simulation. Thin-slice contiguous computed tomographic (CT) angiography is the best source of medical images for construction of 3D models, which requires segmentation of AAA in the images. Existing methods for segmentation of AAA rely on either manual process or 2D segmentation in each 2D CT slide. However, a traditional manual segmentation is a time consuming process which is not practical for routine use. The construction of a 3D model from 2D segmentation of each CT slice is not a fully satisfactory solution due to rough contours that can occur because of lack of constraints among segmented slices, as well as missed segmentation slices. To overcome such challenges, this paper proposes the 3D segmentation of AAA using the concept of variable neighborhood search by iteratively alternating between two different segmentation techniques in the two different 3D search spaces of voxel intensity and voxel gradient. The segmentation output of each method is used as the initial contour to the other method in each iteration. By alternating between search spaces, the technique can escape local minima that naturally occur in each search space. Also, the 3D search spaces provide more constraints across CT slices, when compared with the 2D search spaces in individual CT slices. The proposed method is evaluated with 10 easy and 10 difficult cases of AAA. The results show that the proposed 3D segmentation technique achieves the outstanding segmentation accuracy with an average dice similarity value (DSC) of 91.88%, when compared to the other methods using the same dataset, which are the 2D proposed method, classical graph cut, distance regularized level set evolution, and registration based geometric active contour with the DSCs of 87.57 +/- 4.52%, 72.47 +/- 8.11%, 58.50 +/- 8.86% and 76.21 +/- 10.49%, respectively.
机译：腹主动脉瘤（AAA）的3D模型可以为临床管理和模拟提供有用的解剖信息。薄片连续计算断层摄影（CT）血管造影是用于构建3D模型的最佳医学图像来源，需要在图像中进行AAA的分割。用于分割AAA的现有方法依赖于每个2D CT载玻片中的手动过程或2D分段。但是，传统的手动分段是耗时的过程，不实用的例行使用。从每个CT切片的2D分割的3D模型的构造不是由于粗糙的轮廓而产生的溶液，这可能由于分段切片中缺乏限制以及未错过的分割切片而发生的。为了克服这些挑战，本文提出了使用可变邻域搜索的概念来提出AAA的3D分割，通过体素强度和体素梯度的两个不同的3D搜索空间中的两个不同的分段技术之间迭代交替。每个方法的分割输出用作每次迭代中的其他方法的初始轮廓。通过在搜索空间之间交替，该技术可以在每个搜索空间中自然发生的局部最小值。此外，3D搜索空间在与单个CT切片中的2D搜索空间相比时，跨CT切片提供更多约束。所提出的方法是用10个容易和10个难度的AAA难以评估的方法。结果表明，当使用相同数据集的其他方法相比，所提出的3D分割技术实现了91.88％的平均骰子相似值（DSC）的出色分割精度。正规化级别的进化和基于登记的几何活性轮廓，DSC为87.57 +/- 4.52％，72.47 +/- 8.11％，58.50 +/- 8.86％和76.21 +/- 10.49％。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号