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Lapse observation algorithm for lung cancer detection using 3D thoracic helical CT images

机译:使用3D胸螺旋CT图像进行肺癌检测的流逝观察算法

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In this paper, we present a lapse observation algorithm for lung cancer detection using 3D thoracic helical CT images. Purpose of this study is to detect the interval change that exist between time different images of same patient. We employed two methods to detect the interval change. The first method is 3D local template matching method. We tried to detect the movement of blood vessel and other organs by this method. The second method is subtraction method. We tried to detect the new shadow by this method. The subtraction technique is the common method which detects the interval change. If the two images are produced in an identical manner, the subtraction image derived from a pair of thin slice CT with time difference having an uniform zero pixel value except for regions with interval changes. However, the same 3D thoracic images are not obtained. Therefore, we study the method to correct the location between 3D thoracic images with time difference.
机译:在本文中,我们使用3D胸螺旋CT图像呈现肺癌检测的流失观察算法。本研究的目的是检测相同患者的时间不同图像之间存在的间隔变化。我们采用了两种方法来检测间隔变化。第一种方法是3D本地模板匹配方法。我们试图通过这种方法检测血管和其他器官的运动。第二种方法是减法方法。我们试图通过这种方法检测新的阴影。减法技术是检测间隔变化的常见方法。如果两种图像以相同的方式产生,则从一对薄片CT导出的减法图像,其中具有均匀零像素值的时间差,除了具有间隔变化的区域之外。然而,没有获得相同的3D胸图像。因此,我们研究了纠正了时间差的3D胸图像之间的位置。

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