Effects of CT image segmentation methods on the accuracy of long bone 3D reconstructions
Effects of CT image segmentation methods on the accuracy of long bone 3D reconstructions
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DOI：
10.1016/j.medengphy.2010.10.002
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发表时间：
2011-03-01
影响因子：
2.2
通讯作者：
Schmutz, Beat
中科院分区：
文献类型：
--
作者：
Rathnayaka, Kanchana;Sahama, Tony;Schmutz, Beat
医学研究的许多领域都需要CT扫描数据生成三维骨骼模型，因此对一种准确、易获取的图像分割方法提出了很高的要求。尽管多年来已经发表了许多复杂的分割方法，但大多数方法并不容易为一般研究界所用。因此，本研究旨在量化三种流行的图像分割方法的准确性，即强度阈值分割和Canny边缘检测的两种实现，用于生成长骨三维模型。为了减少与视觉选择阈值相关的用户依赖错误，我们提出了一种基于Canny过滤器选择合适阈值的新方法。使用机械接触式扫描仪和微型CT扫描仪生成参考模型，以验证5只完整羊后肢的CT数据生成的3D骨模型。当考虑骨模型的整体精度时，所研究的三种分割方法产生的结果具有可比性，平均误差在0.18-0.24 mm之间。然而，对于骨骨干，Canny边缘检测和基于Canny滤波的阈值生成的3D模型，与通过视觉选择阈值生成的模型相比，具有更高的精度。本研究表明，可以使用一般研究界可用的相对简单的分割方法生成具有子体素精度的3D模型。(c) 2010年ipm。Elsevier Ltd.出版。版权所有。
An accurate and accessible image segmentation method is in high demand for generating 3D bone models from CT scan data, as such models are required in many areas of medical research. Even though numerous sophisticated segmentation methods have been published over the years, most of them are not readily available to the general research community. Therefore, this study aimed to quantify the accuracy of three popular image segmentation methods, two implementations of intensity thresholding and Canny edge detection, for generating 3D models of long bones. In order to reduce user dependent errors associated with visually selecting a threshold value, we present a new approach of selecting an appropriate threshold value based on the Canny filter. A mechanical contact scanner in conjunction with a microCT scanner was utilised to generate the reference models for validating the 3D bone models generated from CT data of five intact ovine hind limbs. When the overall accuracy of the bone model is considered, the three investigated segmentation methods generated comparable results with mean errors in the range of 0.18-0.24 mm. However, for the bone diaphysis, Canny edge detection and Canny filter based thresholding generated 3D models with a significantly higher accuracy compared to those generated through visually selected thresholds. This study demonstrates that 3D models with sub-voxel accuracy can be generated utilising relatively simple segmentation methods that are available to the general research community. (C) 2010 IPEM. Published by Elsevier Ltd. All rights reserved.