Automatic pulmonary fissure detection and lobe segmentation in CT chest images.
Automatic pulmonary fissure detection and lobe segmentation in CT chest images.
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CT 胸部图像中的自动肺裂检测和肺叶分割。
DOI：
10.1186/1475-925x-13-59
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发表时间：
2014-05-07
影响因子：
3.9
通讯作者：
Kang Y
中科院分区：
文献类型：
--
作者：
Qi S;van Triest HJ;Yue Y;Xu M;Kang Y
多探测器计算机断层扫描已成为诊断慢性呼吸道疾病的宝贵工具。基于CT图像，自动检测肺裂并将肺分为五叶的算法将有助于区域量化肺密度、纹理、气道和血管结构、通气和灌注等。基于血管和支气管的稀疏性，采用矢状面自适应裂隙扫描对潜在裂隙区域进行定位。在冠状切片中采用基于Hessian矩阵的线增强滤波器，通过均匀代价搜索确定最短路径。采用基于径向基函数的隐式曲面拟合提取裂缝表面进行叶瓣分割。通过三个隐裂面功能，将肺分为五个肺叶。该算法在14个数据集上进行了测试。通过平均值（±S.D.）、均方根以及从人工定义的裂缝表面到算法提取的裂缝表面的最短欧几里德距离的最大值来评估精度。所有数据集的平均值（±S.D.）、均方根和最短欧氏距离最大值分别为2.05±1.80、2.46和7.34 mm。右侧水平裂为2.77±2.12、3.13、7.75 mm，左侧斜裂为2.31±1.76、3.25、6.83 mm。裂隙检测对裂隙附近有小肺结节和胸膜下小肺结节的资料有效。计算各肺叶的体积和肺气肿指数。算法速度非常快，对于320片的数据集，完成裂缝检测和裂缝扩展只需要50秒左右。矢状面自适应裂缝扫描可以快速定位潜在裂缝区域。在基于Hessian的线增强滤波器对潜在区域进行增强后，均匀代价搜索可以成功提取二维裂缝。表面拟合能够为每个数据集获得三个隐式表面函数。该算法具有较好的准确性、鲁棒性和速度，可以将病灶定位到各个脑叶中并进行区域分析。
Multi-detector Computed Tomography has become an invaluable tool for the diagnosis of chronic respiratory diseases. Based on CT images, the automatic algorithm to detect the fissures and divide the lung into five lobes will help regionally quantify, amongst others, the lung density, texture, airway and, blood vessel structures, ventilation and perfusion. Sagittal adaptive fissure scanning based on the sparseness of the vessels and bronchi is employed to localize the potential fissure region. Following a Hessian matrix based line enhancement filter in the coronal slice, the shortest path is determined by means of Uniform Cost Search. Implicit surface fitting based on Radial Basis Functions is used to extract the fissure surface for lobe segmentation. By three implicit fissure surface functions, the lung is divided into five lobes. The proposed algorithm is tested by 14 datasets. The accuracy is evaluated by the mean (±S.D.), root mean square, and the maximum of the shortest Euclidian distance from the manually-defined fissure surface to that extracted by the algorithm. Averaged over all datasets, the mean (±S.D.), root mean square, and the maximum of the shortest Euclidian distance are 2.05 ± 1.80, 2.46 and 7.34 mm for the right oblique fissure. The measures are 2.77 ± 2.12, 3.13 and 7.75 mm for the right horizontal fissure, 2.31 ± 1.76, 3.25 and 6.83 mm for the left oblique fissure. The fissure detection works for the data with a small lung nodule nearby the fissure and a small lung subpleural nodule. The volume and emphysema index of each lobe can be calculated. The algorithm is very fast, e.g., to finish the fissure detection and fissure extension for the dataset with 320 slices only takes around 50 seconds. The sagittal adaptive fissure scanning can localize the potential fissure regions quickly. After the potential region is enhanced by a Hessian based line enhancement filter, Uniform Cost Search can extract the fissures successfully in 2D. Surface fitting is able to obtain three implicit surface functions for each dataset. The current algorithm shows good accuracy, robustness and speed, may help locate the lesions into each lobe and analyze them regionally.