北京生物医学工程2012，Vol.31Issue(4)：349-355,7.DOI:10.3969/j.issn.1002-3208.2012.04.04.
基于重采样的胸部CT图像肺实质自动分割
Automatic segmentation of lung parenchyma from thoracic CT based on image resampling
司广磊 1齐守良 1岳勇 2Han J.W.van Triest 1康雁1
作者信息
- 1. 东北大学中荷生物医学与信息工程学院,沈阳,110004
- 2. 中国医科大学盛京医院放射科,沈阳,110004
- 折叠
摘要
Abstract
Automatic lung parenchyma segmentation is one of the most important steps in the computer aided diagnosis (CAD) of the lung. To increase segmentation speed, an algorithm based on resampling of the image data is proposed and implemented. Methods The algorithm firstly resamples and extracts a small part (1/8 ) of the original CT images data. Several steps are implemented to get preliminary segmentation with the resampled data, which include simple threshold segmentation, body region elimination, trachea extraction, removal of interior cavities, left-right lung separation and lung nodule filling. The final results are obtained after projecting the preliminary segmentation to the original dataset and morphology smoothing. The proposed algorithm is applied to 20 patients' data (2556 slices) , and the results are compared to the manual segmentations. Results The algorithm can get accurate results with an average area overlapped ratio 99. 02% to the manual segmentation by the radiologist, and works well for the abnormal cases (right-left
connected, with nodules and uncompleted views) . Through resampling, the time consumption of the algorithm is shortened significantly, typically by 50%, and the processing for one slice image is less than 0. 25 s. Conclusions The proposed automatic lung parenchyma segmentation algorithm with excellent robustness and high speed, can get accurate result and satisfy the requirements of current clinical applications.关键词
肺实质/重采样/CT图像/分割/计算机辅助诊断Key words
lung parenchyma/ resampling/ CT image/ segmentation/ computer aided diagnosis分类
信息技术与安全科学引用本文复制引用
司广磊,齐守良,岳勇,Han J.W.van Triest,康雁..基于重采样的胸部CT图像肺实质自动分割[J].北京生物医学工程,2012,31(4):349-355,7.
