摘要
本文研究一种用于自动检测CT图像中肺结节的计算机辅助检测(CAD)算法。该算法首先从CT图像中分割出肺部区域,然后利用基于图像灰度分布的阈值方法提取出包含肺结节和血管的感兴趣区域(ROIs)。在研究区分肺结节和血管的特征之后,利用基于规则的判别方法将感兴趣区域进行分类并提取出肺结节。运用本算法对232幅CT序列图像进行实验,实验结果表明运用该算法具有高达85％的检出率。
This paper studies a computer-aided detection (CAD) algorithm for automatically detecting lung nodules in CT images. Firstly, the lung areas are segmented from CT images. Then, the regions of interest (ROIs) including nodules and blood vessels in lung areas are extracted by thresholding techniques based on the distribution of the gray levels for the images. After extracting the features to distinguish between nodules and blood vessels, a rule-based classification method is used to classify the ROIs. Finally, the lung nodules can be detected by utilizing the features. The algorithm had been tested with 232 CT images. Experimental results demonstrated that a high detection rate of 85 % could be achieved when the algorithm was applied.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2006年第z3期2265-2267,共3页
Chinese Journal of Scientific Instrument
