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    • 2. 发明申请
    • Lung nodule detection and classification
    • 肺结核检测和分类
    • US20050207630A1
    • 2005-09-22
    • US10504197
    • 2003-02-14
    • Heang-Ping ChanBerkman SahinerLubomir HadjiyskiChuan ZhouNicholas Petrick
    • Heang-Ping ChanBerkman SahinerLubomir HadjiyskiChuan ZhouNicholas Petrick
    • A61B6/03G06F19/00G06K9/00G06T7/00
    • G06T7/0012A61B6/03A61B6/466A61B6/583G06T2207/10081G06T2207/30061
    • A computer assisted method of detecting and classifying lung nodules within a set of CT images includes performing body contour, airway, lung and esophagus segmentation to identify the regions of the CT images in which to search for potential lung nodules. The lungs are processed to identify the left and right sides of the lungs and each side of the lung is divided into subregions including upper, middle and lower subregions and central, intermediate and peripheral subregions. The computer analyzes each of the lung regions to detect and identify a three-dimensional vessel tree representing the blood vessels at or near the mediastinum. The computer then detects objects that are attached to the lung wall or to the vessel tree to assure that these objects are not eliminated from consideration as potential nodules. Thereafter, the computer performs a pixel similarity analysis on the appropriate regions within the CT images to detect potential nodules and performs one or more expert analysis techniques using the features of the potential nodules to determine whether each of the potential nodules is or is not a lung nodule. Thereafter, the computer uses further features, such as speculation features, growth features, etc. in one or more expert analysis techniques to classify each detected nodule as being either benign or malignant. The computer then displays the detection and classification results to the radiologist to assist the radiologist in interpreting the CT exam for the patient.
    • 在一组CT图像中检测和分类肺结节的计算机辅助方法包括执行身体轮廓,气道,肺和食管分割,以识别CT图像的搜索潜在肺结节的区域。 处理肺以识别肺的左侧和右侧,并且将肺的每一侧分为包括上部,中部和下部亚区域以及中央,中间和周边子区域的子区域。 计算机分析每个肺部区域以检测和识别表示纵隔处或附近的血管的三维血管。 然后,计算机检测附着到肺壁或血管树上的物体,以确保这些物体不被考虑为潜在的结节。 此后,计算机对CT图像内的适当区域进行像素相似性分析以检测潜在的结节,并使用潜在结节的特征来执行一个或多个专家分析技术,以确定每个潜在结节是否为肺 结核。 此后,计算机在一个或多个专家分析技术中使用进一步的特征,例如推测特征,生长特征等,以将每个检测到的结节分类为良性或恶性。 然后,计算机将检测和分类结果显示给放射科医师,以协助放射科医师解释患者的CT检查。