A review of medical imaging informatics

被引:19
|
作者
Sinha, U [1 ]
Bui, A [1 ]
Taira, R [1 ]
Dionisio, J [1 ]
Morioka, C [1 ]
Johnson, D [1 ]
Kangarloo, H [1 ]
机构
[1] Univ Calif Los Angeles, Dept Radiol Sci, Telemed Div, Los Angeles, CA 90095 USA
来源
TECHNIQUES IN BIOINFORMATICS AND MEDICAL INFORMATICS | 2002年 / 980卷
关键词
relevant image selection; content based image retrieval; natural language processing; data modeling; data integration; customized visualization;
D O I
10.1111/j.1749-6632.2002.tb04896.x
中图分类号
R-058 [];
学科分类号
摘要
This review of medical imaging informaties is a survey of current developments in an exciting field. The focus is on informatics issues rather than traditional data processing and information systems, such as picture archiving and communications systems (PACS) and image processing and analysis systems. In this review, we address imaging informatics issues within the requirements of an informatics system defined by the American Medical Informatics Association. With these requirements as a framework, we review, in four sections: (1) Methods to present imaging and associated data without causing an overload, including image study summarization, content-based medical image retrieval, and natural language processing of text data. (2) Data modeling techniques to represent clinical data with focus on an image data model, including general-purpose time-based multimedia data models, healthcare-specific data models, knowledge models, and problem-centric data models. (3) Methods to integrate medical data information from heterogeneous clinical data sources. Advances in centralized databases and mediated architectures are reviewed along with a discussion on our efforts at data integration based on peer-to-peer networking and shared file systems. (4) Visualization schemas to present imaging and clinical data: the large volume of medical data presents a daunting challenge for an efficient visualization paradigm. In this section we review current multimedia visualization methods including temporal modeling, problem-specific data organization, including our problem-centric, context and user-specific visualization interface.
引用
收藏
页码:168 / 197
页数:30
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