Suppressing Chest Radiograph Ribs for Improving Lung Nodule Visibility by using Circular Window Adaptive Median Outlier (CWAMO)

IF 0.7 Q3 COMPUTER SCIENCE, THEORY & METHODS
Dnyaneshwar Kanade, J. Helonde
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引用次数: 1

Abstract

— Chest radiograph ribs obstruct lung nodules. To see the nodule under the chest radiograph ribs, remove or suppress them. The paper describes a circular median filter approach for finding outliers in chest radiographs. The method uses 147 Japanese Society of Radiological Technology x-ray pictures (JSRT). Pixels with intensities two standard deviations above the median are median outliers. Contrast-Limited Adaptive Histogram Equalization enhances nodule visibility (CLAHE). The method is tested on modest chest radiographs and compared to the Budapest University Bone Shadow Eliminated X-Ray Dataset methodology. The initial test uses 50 modest chest radiographs (Test 1). The proposed approach is applied after active shape modelling (ASM) lung segmentation. True positive nodules are seen on 89% of chest radiographs of various subtleties. Test-2 and Test-3 used 20 subtlety-level photos. In Test-2, the peak signal-to-noise ratio (PSNR), mean-to-standard deviation ratio (MSR), and universal image quality index (IQI) are evaluated for the full image and compared to the existing algorithm. For all three parameters, the suggested technique outperforms the algorithm. Test-3 computes nodule MSR and compares it to Budapest University's Bone Shadow Eliminated Dataset and original chest radiographs. The new algorithm improved nodule area contrast by 3.83% and 23.94% compared to the original chest radiograph. This approach improves chest radiograph nodule visualization.
利用圆窗自适应中位离群值(CWAMO)抑制胸片肋骨提高肺结节可见性
胸片显示肋骨阻塞肺结节。胸部x线片下看到结节,切除或抑制结节。本文描述了一种用于寻找胸片异常值的圆形中值滤波方法。该方法使用了147张日本放射学会x射线照片(JSRT)。亮度高于中位数两个标准差的像素是中位数异常值。对比度限制自适应直方图均衡化增强结节可见性(CLAHE)。该方法在普通胸片上进行了测试,并与布达佩斯大学骨阴影消除x射线数据集方法进行了比较。最初的测试使用50张适度的胸片(测试1)。该方法在主动形状建模(ASM)肺分割后应用。真阳性结节出现在89%的胸片上。测试2和测试3使用了20张微妙级别的照片。在Test-2中,对完整图像的峰值信噪比(PSNR)、均值与标准差比(MSR)和通用图像质量指数(IQI)进行了评估,并与现有算法进行了比较。对于这三个参数,建议的技术优于算法。Test-3计算结节的MSR,并将其与布达佩斯大学的骨阴影消除数据集和原始胸部x光片进行比较。与原始胸片相比,新算法分别提高了3.83%和23.94%的结节面积对比度。这种方法可以提高胸片上结节的可见性。
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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来源期刊
CiteScore
2.30
自引率
22.20%
发文量
519
期刊介绍: IJACSA is a scholarly computer science journal representing the best in research. Its mission is to provide an outlet for quality research to be publicised and published to a global audience. The journal aims to publish papers selected through rigorous double-blind peer review to ensure originality, timeliness, relevance, and readability. In sync with the Journal''s vision "to be a respected publication that publishes peer reviewed research articles, as well as review and survey papers contributed by International community of Authors", we have drawn reviewers and editors from Institutions and Universities across the globe. A double blind peer review process is conducted to ensure that we retain high standards. At IJACSA, we stand strong because we know that global challenges make way for new innovations, new ways and new talent. International Journal of Advanced Computer Science and Applications publishes carefully refereed research, review and survey papers which offer a significant contribution to the computer science literature, and which are of interest to a wide audience. Coverage extends to all main-stream branches of computer science and related applications
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