Cervical vertebral corner detection using haar-like features and modified hough forest
Cervical vertebral corner detection using haar-like features and modified hough forest
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DOI：
10.1109/ipta.2015.7367179
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发表时间：
2015-11
期刊：
影响因子：
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通讯作者：
S. Masudur Rahman Al Arif;Muhammad Asad;K. Knapp;M. Gundry;Greg Slabaugh
中科院分区：
文献类型：
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作者：
S. Masudur Rahman Al Arif;Muhammad Asad;K. Knapp;M. Gundry;Greg Slabaugh
颈部(颈椎)是人体的一个灵活部位，特别容易受伤。怀疑颈椎损伤的患者通常使用侧位X线片进行成像。基于这些图像的错误诊断可能会导致严重的长期后果。我们的首要目标是开发一种计算机辅助检测系统，以帮助急诊室医生正确诊断患者的损伤。本文提出了一种在90张颈椎侧位X线片上定位颈椎角的方法。类Haar特征是使用强度和梯度图像块来计算的，每个图像块使用改进的Hough森林回归技术投票选择可能的角点位置。利用二维核密度估计对选票进行聚合，找出角点的位置。我们的方法显示了令人满意的结果，识别角点的平均中位误差为2.08 mm。
The neck (cervical spine) is a flexible part of the human body and is particularly vulnerable to injury. Patients suspected of cervical spine injuries are often imaged using lateral view radiographs. Incorrect diagnosis based on these images may lead to serious long-term consequences. Our overarching goal is to develop a computer-aided detection system to help an emergency room physician correctly diagnose a patient's injury. In this paper, we present a method to localize the corners of cervical vertebrae in a set of 90 lateral cervical radiographs. Haar-like features are computed using intensity and gradient image patches, each of which votes for possible corner position using a modified Hough forest regression technique. Votes are aggregated using two dimensional kernel density estimation, to find the location of the corner. Our method demonstrates promising results, identifying corners with an average median error of 2.08 mm.