Semi-automatic detection of cervical vertebrae in X-ray images using generalized hough transform

M. A. Larhmam, S. Mahmoudi, M. Benjelloun
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引用次数: 34

Abstract

Vertebra detection presents the first step of any automatic spinal column diagnosis. This task becomes more difficult in the case of the cervical X-ray images characterized by their low contrasts and noise due to skull bones. In this paper, we describe an efficient modified template matching method for detecting cervical vertebrae using Generalized Hough Transform (GHT). The proposed method consists of three main steps toward vertebrae detection: 1) Offline training to obtain a robust average model of cervical vertebra. 2) Detecting the potential vertebra centers. 3) Adaptive Post-processing filter. X-ray Image data of 40 healthy cases were used to validate our approach by using a total of 200 cervical vertebrae. We obtained an accuracy of 89%.
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基于广义霍夫变换的x射线图像中颈椎的半自动检测
椎体检测是任何自动脊柱诊断的第一步。在颈椎x线图像的情况下,由于颅骨的低对比度和噪声,这项任务变得更加困难。本文提出了一种基于广义霍夫变换(GHT)的改进模板匹配检测颈椎的方法。本文提出的方法包括三个主要步骤:1)离线训练,获得鲁棒的颈椎平均模型。2)检测潜在椎体中心。3)自适应后处理滤波器。使用40例健康病例的x线图像数据,共使用200个颈椎来验证我们的方法。我们获得了89%的准确率。
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