Carro Silvio Antonio, Scharcanski Jacob
Faculdade de Informática, Universidade do Oeste Paulista (UNOESTE),19.100-00, Presidente Prudente, SP, Brazil.
Comput Biol Med. 2006 Apr;36(4):327-38. doi: 10.1016/j.compbiomed.2004.10.004.
The web has become such an extensive health information repository in the world that it is increasingly difficult to search for relevant medical information. Most medical information available on the web is not peer reviewed, and is retrieved imprecisely by current web search mechanisms (i.e. based on keywords). This paper presents the MedISeek metadata model that allows one to describe medical visual information (i.e. medical images) of different modalities, including their properties, components, relationships and authorship. The model uses the web architecture and supports the international classification of diseases and related health problems (i.e. ICD-10). An RDF schema (Resource Description Framework (RDF), http://www.w3.org/RDF/.) derived from this metadata model is integrated to each medical image, and specifies the semantics of each property in the image. Thus, relevant information can be extracted directly from the images, and data integrity is better preserved in the web. A prototype, presented here, has been built to validate the metadata model, and the mechanism for medical visual information exchange on the web. Our preliminary experimental results indicate that authorized users of our system have been able to describe, store and retrieve medical images and their associated diagnostic information.
网络已成为全球范围内如此广泛的健康信息库，以至于搜索相关医学信息变得越来越困难。网络上的大多数医学信息未经同行评审，并且通过当前的网络搜索机制（即基于关键词）检索不准确。本文提出了MedISeek元数据模型，该模型允许人们描述不同模态的医学视觉信息（即医学图像），包括其属性、组成部分、关系和作者信息。该模型采用网络架构并支持国际疾病及相关健康问题分类（即ICD-10）。从这个元数据模型派生的RDF模式（资源描述框架（RDF），http://www.w3.org/RDF/.）被集成到每个医学图像中，并指定图像中每个属性的语义。因此，可以直接从图像中提取相关信息，并且数据完整性在网络中得到更好的保存。这里展示的一个原型已构建完成，用于验证元数据模型以及网络上医学视觉信息交换的机制。我们的初步实验结果表明，我们系统的授权用户能够描述、存储和检索医学图像及其相关的诊断信息。
