FILTER SELECTION FOR REMOVING NOISE FROM CT SCAN IMAGES USING DIGITAL IMAGE PROCESSING ALGORITHM

IF 0.6 Q4 ENGINEERING, BIOMEDICAL

Biomedical Engineering: Applications, Basis and Communications Pub Date : 2023-11-22 DOI:10.4015/s1016237223500382

A. Siddiqi

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引用次数: 0

Abstract

Image de-noising is an essential tool for removing unwanted signals from an image. In Computed Tomography (CT) images, the image quality is degraded by the absorption of X-rays and quantum noise, which is generated due to the excitement of X-ray photons. Removal of noise and preservation of information in the CT images becomes a challenge for an imaging algorithm design. During the algorithm design selection of dataset is an important aspect for deducing results. The dataset used in this research comprises of 60 CT scan images of liver cancer archived from the arterial contrast enhanced phase. In this phase the cancer cells appear more intense as compared to the healthy liver tissue due to the absorption of contrast enhancing reagent. The experimentation for appropriate noise removal filter selection is done by testing the images using Mean, Median and Weiner Filters. The filter selected should give an image output which has minimal randomness, sharper boundaries and no blur. The de-noised image will provide a better visibility of the disease to the radiologist and physician. The performance parameters used for the assessment of various filters used in the study include visual assessment, entropy and signal to noise ratio (SNR) of the images. Median filter gives an accuracy of 96%, mean filter is 76.2% accurate with respect to original information and Weiner filters has an accuracy of 79.7%.

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利用数字图像处理算法选择滤波器去除 CT 扫描图像中的噪声

图像去噪是去除图像中不需要的信号的重要工具。在计算机断层扫描（CT）图像中，图像质量会因 X 射线的吸收和量子噪声而下降，量子噪声是由于 X 射线光子的激发而产生的。去除 CT 图像中的噪声并保留其信息成为成像算法设计的一项挑战。在算法设计过程中，数据集的选择是推导结果的一个重要方面。本研究使用的数据集包括 60 张动脉造影剂增强阶段存档的肝癌 CT 扫描图像。在这一阶段，由于吸收了对比度增强试剂，与健康的肝脏组织相比，癌细胞的密度更高。通过使用平均值滤波器、中值滤波器和韦纳滤波器对图像进行测试，以选择合适的去噪滤波器。所选滤波器输出的图像应具有最小的随机性、更清晰的边界和无模糊。去噪后的图像将为放射科医生和内科医生提供更好的疾病可见度。用于评估研究中使用的各种滤波器的性能参数包括图像的视觉评估、熵和信噪比（SNR）。中值滤波器的准确率为 96%，平均滤波器对原始信息的准确率为 76.2%，而韦纳滤波器的准确率为 79.7%。

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

Biomedical Engineering: Applications, Basis and Communications Biochemistry, Genetics and Molecular Biology-Biophysics

CiteScore

1.50

自引率

11.10%

发文量

审稿时长

4 months

期刊介绍： Biomedical Engineering: Applications, Basis and Communications is an international, interdisciplinary journal aiming at publishing up-to-date contributions on original clinical and basic research in the biomedical engineering. Research of biomedical engineering has grown tremendously in the past few decades. Meanwhile, several outstanding journals in the field have emerged, with different emphases and objectives. We hope this journal will serve as a new forum for both scientists and clinicians to share their ideas and the results of their studies. Biomedical Engineering: Applications, Basis and Communications explores all facets of biomedical engineering, with emphasis on both the clinical and scientific aspects of the study. It covers the fields of bioelectronics, biomaterials, biomechanics, bioinformatics, nano-biological sciences and clinical engineering. The journal fulfils this aim by publishing regular research / clinical articles, short communications, technical notes and review papers. Papers from both basic research and clinical investigations will be considered.