用于诊断人类呼吸道传染病COVID-19的计算机断层扫描图像处理程序的开发

M. Boopathi, D. Khanna, R. Vennila, R. Rajan, T. Maidili, S. Pooja, K. Jothimeena, A. Aarthi, R. Megala, P. Venkatraman
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引用次数: 0

摘要

计算机断层扫描(CT)是一种非侵入性的方法,它可以在不叠加端到端结构的情况下给出人体各个部位的CT图像。CT测量中的一些问题限制了很少的参数,如量子噪声、光束硬化、患者的x射线散射和非线性部分体积效应。使用Adobe Photoshop, ImageJ和Origin软件进行图像处理,以获得用于数值分析的高质量图像。统计功能允许调查人类呼吸道感染疾病的一般特征。利用自动诊断系统,可以借助CT图像过滤出疾病的分化。数据可以从CT图像中分析,以区分人类呼吸道感染疾病,一种常见的疾病,如重度抑郁症(MD)或强迫症(OCD)和正常肺。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Computed Tomography Image Processing Procedure for the Diagnosis of Human Respiratory Infectious Diseases: COVID-19
Computed Tomography (CT) is a non-invasive method to give CT images of every part of the human body without superimposition of end-to-end structures. Some issues in measurements with CT are limiting too few parameters like quantum noise, beam hardening, X-ray scattering by the patient, and nonlinear partial volume effects. Image processing with Adobe Photoshop, ImageJ, and Origin software have been used to achieve good quality images for numerical analysis. Statistical functions permit to investigate the general characteristics of a human respiratory infections disease. Using Automatic Diagnosis system, differentiation in diseases can be filtered out with the help of CT images. Data can be analyzed from the CT images to distinguish between a human respiratory infections disease, a common disorder like Major Depression (MD) or Obsessive-Compulsive Disorder (OCD) and a normal lung.
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