A Method for Enhancing Lung Nodules in Chest Radiographs by Use of LoG Filter

Zhenghao Shi, Jun Bai, Lifeng He, Tsuyoshi Nakamura, Quanzhu Yao, H. Itoh
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引用次数: 5

Abstract

To make the visual of any region with a spherical structure (where a potential nodule may happen to occur) in lung fields in a chest radiograph more clearly and to better determine the extent of that region and the presence of any other region of the same nature, this paper proposes a method for enhancing lung nodules in chest radiograph images by use of Laplace of Gaussian (LoG) filter. The key for the implementation of the method is the selection of the standard deviation of the LoG kernel. After LoG filter convolution on a chest radiograph image, regions of high circularity in the image are enhanced, while other regions are suppressed, and thus the contrast between nodules and normal anatomy is improved. With respect to other methods, the main advantage of LoG filter based method is that no prior explicit knowledge about the actual shape of the nodules and structure of image background is needed. The methods have been tested on a publicly available database of 52 chest radiographs, in which the absence and presence of nodules in the chest radiographs were confirmed by use of CT examinations. Experimental results demonstrate that the proposed method in enhancing lung nodules in chest radiographs is efficient and effective.
利用LoG滤波器增强胸片上肺结节的方法
为了使胸片肺场中任何具有球形结构的区域(可能发生潜在结节的区域)的视觉更清晰,更好地确定该区域的范围和其他相同性质的区域的存在,本文提出了一种利用拉普拉斯高斯(LoG)滤波器增强胸片图像中肺结节的方法。该方法实现的关键是LoG核标准差的选择。对胸片图像进行LoG滤波器卷积后,图像中高圆度的区域得到增强,而其他区域被抑制,从而提高了结节与正常解剖的对比度。与其他方法相比,基于LoG滤波器的方法的主要优点是不需要事先明确了解结节的实际形状和图像背景的结构。这些方法已在公开的52张胸片数据库中进行了测试,其中胸片上结节的存在和消失是通过使用CT检查来确认的。实验结果表明,该方法对胸片上肺结节的增强是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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