Knowledge-based method for segmentation and analysis of lung boundaries in chest X-ray images
Knowledge-based method for segmentation and analysis of lung boundaries in chest X-ray images
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DOI：
10.1016/s0895-6111(98)00051-2
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发表时间：
1998-11-01
影响因子：
5.7
通讯作者：
Sun, CM
中科院分区：
文献类型：
--
作者：
Brown, MS;Wilson, LS;Sun, CM
我们提出了一种基于知识的方法来分割和分析肺部边界的胸部X射线。使用参数特征将图像边缘与肺边界的解剖模型匹配。开发了一个模块化的系统架构，其中包括模型，图像处理例程，推理机和黑板。与肺边界相关联的边缘被自动识别并且异常特征被报告。在对14张图像进行的初步测试中，与经验丰富的放射科医生的评估相比，该系统显示出88%的灵敏度和95%的特异性。(C)1999爱思唯尔科技有限公司。保留所有权利。
We present a knowledge-based approach to segmentation and analysis of the lung boundaries in chest X-rays. Image edges are matched to an anatomical model of the lung boundary using parametric features. A modular system architecture was developed which incorporates the model, image processing routines, an inference engine and a blackboard. Edges associated with the lung boundary are automatically identified and abnormal features are reported. In preliminary testing on 14 images for a set of 18 detectable abnormalities, the system showed a sensitivity of 88% and a specificity of 95% when compared with assessment by an experienced radiologist. (C) 1999 Elsevier Science Ltd. All rights reserved.