Content-Based Image Retrieval in Medicine: Retrospective Assessment, State of the Art, and Future Directions.

Pub Date : 2009-01-01 DOI:10.4018/jhisi.2009010101
L Rodney Long, Sameer Antani, Thomas M Deserno, George R Thoma
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引用次数: 80

Abstract

Content-based image retrieval (CBIR) technology has been proposed to benefit not only the management of increasingly large image collections, but also to aid clinical care, biomedical research, and education. Based on a literature review, we conclude that there is widespread enthusiasm for CBIR in the engineering research community, but the application of this technology to solve practical medical problems is a goal yet to be realized. Furthermore, we highlight "gaps" between desired CBIR system functionality and what has been achieved to date, present for illustration a comparative analysis of four state-of-the-art CBIR implementations using the gap approach, and suggest that high-priority gaps to be overcome lie in CBIR interfaces and functionality that better serve the clinical and biomedical research communities.

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医学中基于内容的图像检索:回顾评估、技术现状和未来方向。
基于内容的图像检索(CBIR)技术不仅有利于管理日益庞大的图像集,而且有助于临床护理、生物医学研究和教育。通过文献综述,我们得出结论,在工程研究界对CBIR有着广泛的热情,但将该技术应用于解决实际医学问题是一个尚未实现的目标。此外,我们强调了期望的CBIR系统功能与迄今为止取得的成果之间的“差距”,使用差距方法对四种最先进的CBIR实现进行了比较分析,并提出需要克服的高优先级差距在于CBIR接口和功能,以便更好地服务于临床和生物医学研究界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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