Selective enhancement filters for nodules, vessels, and airway walls in two- and three-dimensional CT scans
Selective enhancement filters for nodules, vessels, and airway walls in two- and three-dimensional CT scans
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DOI：
10.1118/1.1581411
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发表时间：
2003-08-01
期刊：
影响因子：
3.8
通讯作者：
Doi, K
中科院分区：
文献类型：
--
作者：
Li, Q;Sone, S;Doi, K
计算机辅助诊断（CAD）方案已被开发，以协助放射科医生在早期发现肺癌的放射照片和计算机断层扫描（CT）图像。为了提高结节检测的灵敏度，许多研究人员采用滤波器作为结节增强的预处理步骤。然而，这些过滤器不仅可以增强结节，还可以增强其他解剖结构，如肋骨、血管和气道壁。因此，结节的检测通常会伴随着这些正常解剖结构引起的大量假阳性。在这项研究中，我们开发了三种用于点、线和平面的选择性增强过滤器，可以同时增强特定形状的对象（例如，点状结节）并抑制其他形状的对象（例如，线状血管）。因此，作为预处理步骤，这些过滤器将有助于提高结节检测的灵敏度和减少假阳性的数量。我们将增强滤波器应用于合成图像，以证明它们可以选择性地增强特定形状并抑制其他形状。我们还将我们的增强滤波器应用于真实的二维（2D）和三维（3D）CT图像，以显示其在增强真实的医学图像中的特定对象的有效性。我们相信，在这项研究中开发的三个增强过滤器将是有用的，在计算机检测癌症的2D和3D医学图像。(C)2003年美国医学物理学家协会。
Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists in the early detection of lung cancer in radiographs and computed tomography (CT) images. In order to improve sensitivity for nodule detection, many researchers have employed a filter as a preprocessing step for enhancement of nodules. However, these filters enhance not only nodules, but also other anatomic structures such as ribs, blood vessels, and airway walls. Therefore, nodules are often detected together with a large number of false positives caused by these normal anatomic structures. In this study, we developed three selective enhancement filters for dot, line, and plane which can simultaneously enhance objects of a specific shape (for example, dot-like nodules) and suppress objects of other shapes (for example, line-like vessels). Therefore, as preprocessing steps, these filters would be useful for improving the sensitivity of nodule detection and for reducing the number of false positives. We applied our enhancement filters to synthesized images to demonstrate that they can selectively enhance a specific shape and suppress other shapes. We also applied our enhancement filters to real two-dimensional (2D) and three-dimensional (3D) CT images to show their effectiveness in the enhancement of specific objects in real medical images. We believe that the three enhancement filters developed in this study would be useful in the computerized detection of cancer in 2D and 3D medical images. (C) 2003 American Association of Physicists in Medicine.