Lung field segmenting in dual-energy subtraction chest X-ray images.
Lung field segmenting in dual-energy subtraction chest X-ray images.
复制标题
双能减影胸部 X 射线图像中的肺场分割。
DOI：
10.1007/s10278-003-1701-8
复制
发表时间：
2004
影响因子：
4.4
通讯作者：
Alvarez,RobertE
中科院分区：
文献类型：
--
作者：
Alvarez,RobertE
本研究的目的是开发和测试一种方法来描绘肺野边界的双能量胸部X射线图像。分割方法使用软组织图像和空间频率相关的背景减除图像。定位大规模胸部解剖特征，并用于选择肺尖、外侧肺边界以及肺-纵隔和肺-隔膜边界。轮廓的无关部分被移除，并且它们被连接以形成完整的肺边界。可靠性测量使用统计形状模型来估计轮廓出现的概率。该方法进行了实验测试与30人的主题图像。它具有更高的准确性和特异性和灵敏度参数等于最好的以前报道的方法。可靠性测量能够检测具有不寻常的肺轮廓或处理中的错误的轮廓。该方法利用双能量减影图像的特点，以提高肺野分割性能。
The purpose of this study was to develop and test a method to delineate lung field boundaries in dual-energy chest x-ray images. The segmenting method uses soft-tissue images and spatial frequency–dependent, background-subtracted images. Large-scale chest anatomy features are located and used to select the lung apices, the lateral lung boundaries, and the lung–mediastinum and lung–diaphragm boundaries. Extraneous parts of the contours are removed and they are joined to form complete lung boundaries. The reliability measure uses a statistical shape model to estimate the probability of occurrence of a contour. The method was experimentally tested with 30 human subject images. It has higher accuracy and specificity and a sensitivity parameter equal to the best previously reported method. The reliability measure is able to detect contours with unusual lung outlines or errors in the processing. The method exploits the characteristics of dual-energy subtraction images to improve lung field segmenting performance.