Pulmonary Disease Census Aiding System Based on Medical Image Grid

Hai Jin, Aobing Sun, Qin Zhang, Ran Zheng, R. He
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Abstract

The large population exerts high burdens to Chinese health census works. In this paper, we propose our PDCAS (Pulmonary Disease Census Aiding System) based on Medical Image Grid, which aims to utilize the superiorities of grid technology to improve the efficiency of high-incidence and occupational pulmonary disease census. PDCAS integrates the individual medical information distributed in different hospitals’ information systems into Medical Information Centre of one area. The census records are classified through one risk rate based cross clustering model to direct the medical diagnosis and review. The main processing algorithms of PDCAS are subdivided and encapsulated as detachable web services with adapted granularity to support the grid workflow composition corresponding to different pulmonary diseases or aiding aims. The prototype of PDCAS proves the possible improvement of grid technology to diseases census and other data intensive medical applications.
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基于医学图像网格的肺部疾病普查辅助系统
中国人口众多,给健康普查工作带来了沉重的负担。本文提出了一种基于医学图像网格的肺病普查辅助系统(PDCAS),旨在利用网格技术的优势,提高高发和职业性肺病普查的效率。PDCAS将分布在不同医院信息系统中的个体医疗信息整合到一个区域的医疗信息中心。通过一种基于风险率的交叉聚类模型对人口普查记录进行分类,指导医疗诊断和复查。PDCAS的主要处理算法被细分并封装为可分离的web服务,并具有自适应的粒度,以支持不同肺部疾病或辅助目标对应的网格工作流组合。PDCAS的原型验证了网格技术在疾病普查和其他数据密集型医疗应用中的可能改进。
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