首页> 外文期刊>Journal of digital imaging: the official journal of the Society for Computer Applications in Radiology >Automatic estimation of orientation and position of spine in digitized X-rays using mathematical morphology
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Automatic estimation of orientation and position of spine in digitized X-rays using mathematical morphology

机译:使用数学形态学自动估计数字化X射线中脊柱的方向和位置

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摘要

In this paper, we propose a method for automatic determination of position and orientation of spine in digitized spine X-rays using mathematical morphology. As the X-ray images are usually highly smeared, vertebrae segmentation is a complex process. The image is first coarsely segmented to obtain the location and orientation information of the spine. The state-of-the-art technique is based on the deformation model of a template, and as the vertebrae shape usually shows variation from case to case, accurate representation using a template is a difficult process. The proposed method makes use of the vertebrae morphometry and gray-scale profile of the spine. The top-hat transformation-based method is proposed to enhance the ridge points in the posterior boundary of the spine. For cases containing external objects such as ornaments, H-Maxima transform is used for segmentation and removal of these objects. The Radon transform is then used to estimate the location and orientation of the line joining the ridge point clusters appearing on the boundary of the vertebra body. The method was validated for 100 cervical spine X-ray images, and in all cases, the error in orientation was within the accepted tolerable limit of 15 degrees. The average error was found to be 4.6 degrees. A point on the posterior boundary was located with an accuracy of +/-5.2 mm. The accurate information about location and orientation of the spine is necessary for fine-grained segmentation of the vertebrae using techniques such as active shape modeling. Accurate vertebrae segmentation is needed in successful feature extraction for applications such as content-based image retrieval of biomedical images.
机译:在本文中,我们提出了一种使用数学形态学自动确定数字化脊柱X射线中脊柱位置和方向的方法。由于X射线图像通常高度涂抹,因此椎骨分割是一个复杂的过程。首先将图像粗略分割,以获得脊柱的位置和方向信息。最新技术基于模板的变形模型,并且由于椎骨形状通常会因情况而异,因此使用模板进行精确表示是一个困难的过程。所提出的方法利用了脊椎的椎骨形态和灰度轮廓。提出了一种基于高顶变换的方法来增强脊柱后边界的脊点。对于包含外部对象(例如装饰物)的情况,H-Maxima变换用于分割和移除这些对象。然后,使用Radon变换来估计连接出现在椎体边界上的山脊点群集的线的位置和方向。该方法已针对100例颈椎X射线图像进行了验证,并且在所有情况下,方向误差均在公认的15度容许范围内。发现平均误差为4.6度。后边界上的一个点的定位精度为+/- 5.2 mm。有关脊椎位置和方向的准确信息对于使用主动形状建模等技术对椎骨进行精细细分是必要的。在成功的特征提取中,对于诸如基于内容的生物医学图像图像检索等应用,需要准确的椎骨分割。

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