An Approach to Segment Computed Tomography Images using Bat Algorithm

F.R. Amirtha Priyadharshini, N. Hariprasad, S. Asvitha, V. Anandhi, A. Priyadarshini
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引用次数: 0

Abstract

Image evaluation actions are extensively applied to inspect a class of medical pictures recorded with a dedicated imaging approach. This work presents an automated computer assisted technique to mine and assess the Region of Interest (ROI) of Computed Tomography (CT) images. In this work, combination of multi-thresholding and the segmentation scheme is implemented to extract the ROI from Brain and Lung CT images. The multi-thresholding is implemented using Bat Algorithm (BA) and the Kapur’s function and the segmentation is implemented with the level set (DRLS). After extracting the ROI from the CT pictures, the region properties of the ROI is evaluated using the GLCM features. The experimental result of this study confirms that, proposed approach is very efficient in extracting the ROI from the considered CT images. In future, this methodology can be used in hospitals to examine the real CT images.
一种基于Bat算法的计算机断层图像分割方法
图像评价行动被广泛应用于检查一类医学图像记录与专用成像方法。这项工作提出了一种自动化的计算机辅助技术来挖掘和评估计算机断层扫描(CT)图像的兴趣区域(ROI)。本文采用多阈值分割和分割相结合的方法对脑、肺CT图像进行ROI提取。采用Bat算法(BA)和Kapur函数实现多阈值分割,采用水平集(DRLS)实现分割。从CT图像中提取感兴趣区域后,利用GLCM特征评估感兴趣区域的区域属性。本研究的实验结果证实,本文提出的方法可以非常有效地从考虑的CT图像中提取感兴趣区域。未来,该方法可用于医院检查真实的CT图像。
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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