Automatic Lung Segmentation in CT Images Using Anisotropic Diffusion and Morphology Operation
Automatic Lung Segmentation in CT Images Using Anisotropic Diffusion and Morphology Operation
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DOI：
10.1109/cit.2007.143
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发表时间：
2007-10
期刊：
影响因子：
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通讯作者：
HyeSuk Kim;H. Yoon;K. Trung;Gueesang Lee
中科院分区：
文献类型：
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作者：
HyeSuk Kim;H. Yoon;K. Trung;Gueesang Lee
大多数用于识别肺部疾病的计算机辅助诊断（CAD）系统的预处理步骤是肺部分割。本文提出了一种基于各向异性扩散和形态学运算的肺部分割方法。所提出的方法包括三个步骤。第一步，由输入图像生成灰度图像。然后对灰度图像进行各向异性扩散模糊处理。第二步是进行形态学操作，去除气道和纵隔，得到左右肺区域。在第三步骤，生成在第二步骤中获得的右肺区域和左肺区域的二值图像，并将其与原始图像进行匹配以分割肺部分。所提出的方法消除了寻找最佳阈值和分离附接的左肺和右肺的任务。我们已经将我们的新方法应用于几个肺部CT图像，结果表明，这种方法的速度，鲁棒性和准确性。
The preprocessing step of most computer-aided diagnosis (CAD) systems for identifying the lung diseases is lung segmentation. We present a novel lung segmentation technique based on anisotropic diffusion and morphological operation which is performed fast and accurately. The proposed method consists of three steps. At first step, gray image is produced by the input image. And then anisotropic diffusion is preformed to blur the gray image. The second step is that morphological operation is performed to remove the airway and mediastinum and get the right and left lung area. At the third step, the binary image of the right and left lung area obtained in the second step is generated and is matched to the original to segment the lung part. The proposed method eliminates the tasks of finding an optimal threshold and separating the attached left and right lungs. We have applied our new approach on several pulmonary CT images and the results reveal the speed, robustness and accuracy of this method.