Does a CBIR system really impact decisions of physicians in a clinical environment?

Marcelo Ponciano-Silva, Juliana P. Souza, P. Bugatti, M. Bedo, D. S. Kaster, R. Braga, A. Bellucci, P. M. A. Marques, C. Traina, A. Traina
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引用次数: 17

Abstract

Content-based image retrieval systems are employed in several areas. One of the most prominent area is the medical field, due to the huge volume of digital images daily generated in healthcare institutions employed for decision making. There are several works applying CBIR techniques over medical images. However, the great majority of them do not verify whether the systems are actually considered by the specialists as a pontential aid in a real environment. In order to fill this research void in the literature, this work explores user experiments in a CBIR system involving resident physicians and radiologists. To do so, we developed a CBIR system according to requirements provided by the specialists and employed a methodology to analyze the effectiveness of the system for supporting them in clinical routine. The methodology aims at evaluating the system's impact in the user's decision, inquiring the specialists about the image classification and their degree of certainty in different situations using the system. By analyzing the obtained results we can argue that the proposed methodology joined with our medical CBIR system presented a high acceptance and viability rate regarding the radiologists interests in the clinical practice domain, providing a novel approach to analyze CBIR systems under realistic conditions.
在临床环境中,CBIR系统真的会影响医生的决策吗?
基于内容的图像检索系统应用于多个领域。其中最突出的领域是医疗领域,因为医疗机构每天都会产生大量用于决策的数字图像。有几部作品将CBIR技术应用于医学图像。然而,他们中的绝大多数人并没有验证专家是否真的认为这些系统在真实环境中是一种潜在的帮助。为了填补这一研究空白,本研究探索了一个涉及住院医师和放射科医生的CBIR系统的用户实验。为此,我们根据专家提供的要求开发了一套CBIR系统,并采用了一种方法来分析该系统在临床常规中支持他们的有效性。该方法旨在评估系统对用户决策的影响,询问专家关于图像分类及其在不同情况下使用系统的确定性程度。通过分析所获得的结果,我们可以认为,所提出的方法与我们的医疗CBIR系统结合在一起,在临床实践领域提供了放射科医生感兴趣的高接受度和可行性,为在现实条件下分析CBIR系统提供了一种新颖的方法。
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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