首页> 外文会议>PACS and Imaging Informatics; Progress in Biomedical Optics and Imaging; vol.7 no.31 >Computer-aided diagnosis workstation and database system for chest diagnosis based on multihelical CT images
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Computer-aided diagnosis workstation and database system for chest diagnosis based on multihelical CT images

机译:基于多螺旋CT图像的胸腔诊断计算机辅助诊断工作站和数据库系统

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Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.
机译:多螺旋CT扫描仪以采集胸部CT图像进行大规模筛查的速度显着前进。基于多螺旋CT图像的质量筛选需要读取大量图像。正是这一耗时的步骤使得目前无法使用螺旋CT进行质量筛查。为了克服这个问题,我们通过开发自动在螺旋CT图像中检测可疑肺癌的肺癌筛查算法和自动检测可疑冠状动脉钙化的冠状动脉钙化筛查算法,为医学筛查专家提供了诊断辅助方法。我们还通过使用虚拟专用网络路由器和生物特征指纹认证系统以及生物特征面部认证系统为医疗信息的安全性开发了两个或多个地区的社区健康电子医疗记录系统和原型互联网系统。基于这些诊断辅助方法,我们现在已经开发了一种新的计算机辅助工作站和数据库,可以在短时间内三维显示可疑病变。本文介绍了为评估此新系统而进行的基础研究。这项研究的结果表明,我们的计算机辅助诊断工作站和网络系统可以提高诊断速度,诊断准确性和医疗信息的安全性。

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