Endoscopic image analysis in semantic space.
Endoscopic image analysis in semantic space.
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DOI：
10.1016/j.media.2012.04.010
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发表时间：
2012-10
影响因子：
10.9
通讯作者：
Wrba, F.
中科院分区：
文献类型：
--
作者：
Kwitt, R.;Vasconcelos, N.;Rasiwasia, N.;Uhl, A.;Davis, B.;Haefner, M.;Wrba, F.
提出了一种新的方法来设计一个语义，低维，编码内窥镜图像。这种编码基于场景识别的最新进展，其中图像内容的语义建模在过去十年中获得了相当大的关注。虽然场景的语义主要包括环境概念，如植被、山脉或天空，但内窥镜图像的语义是医学相关的视觉元素，如息肉、特殊表面图案或血管结构。所提出的语义编码不同于内窥镜图像分析（用于医疗决策支持）中常用的表示，因为它建立了一个语义空间，其中每个坐标轴都有一个清晰的人类解释。它还表明，建立一个连接到黎曼几何，这使得原则上的解决方案，出现在医生培训和临床实践中的一些问题。通过利用来自信息几何的结果来利用这种连接，以解决诸如1）重要语义概念的识别、2）语义聚焦的图像浏览以及3）针对共享医学相关视觉细节的图像集合的平均情况语义编码的估计的问题。该方法可以为医生提供易于解释的视觉内容的语义编码，在此基础上可以自然地执行进一步的决策或操作。这与用于医疗决策支持的内窥镜图像分析中的普遍实践相反，在内窥镜图像分析中，图像内容主要由具有区分能力但缺乏人类可解释性的有区别的、高维的外观特征捕获。
A novel approach to the design of a semantic, low-dimensional, encoding for endoscopic imagery is proposed. This encoding is based on recent advances in scene recognition, where semantic modeling of image content has gained considerable attention over the last decade. While the semantics of scenes are mainly comprised of environmental concepts such as vegetation, mountains or sky, the semantics of endoscopic imagery are medically relevant visual elements, such as polyps, special surface patterns, or vascular structures. The proposed semantic encoding differs from the representations commonly used in endoscopic image analysis (for medical decision support) in that it establishes a semantic space, where each coordinate axis has a clear human interpretation. It is also shown to establish a connection to Riemannian geometry, which enables principled solutions to a number of problems that arise in both physician training and clinical practice. This connection is exploited by leveraging results from information geometry to solve problems such as 1) recognition of important semantic concepts, 2) semantically-focused image browsing, and 3) estimation of the average-case semantic encoding for a collection of images that share a medically relevant visual detail. The approach can provide physicians with an easily interpretable, semantic encoding of visual content, upon which further decisions, or operations, can be naturally carried out. This is contrary to the prevalent practice in endoscopic image analysis for medical decision support, where image content is primarily captured by discriminative, high-dimensional, appearance features, which possess discriminative power but lack human interpretability.
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DOI：
10.1023/b:visi.0000029664.99615.94
发表时间：
2004-11-01
影响因子：
19.5
作者：
Lowe, DG
通讯作者：
Lowe, DG
DOI：
10.1111/j.2517-6161.1977.tb01600.x
发表时间：
1977-01-01
期刊：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL
影响因子：
--
作者：
DEMPSTER, AP;LAIRD, NM;RUBIN, DB
通讯作者：
RUBIN, DB
影响因子：
10.9
作者：
Haefner, M.;Liedlgruber, M.;Uhl, A.;Vecsei, A.;Wrba, F.
通讯作者：
Wrba, F.
影响因子：
3.4
作者：
KUDO, S;HIROTA, S;YAGYUU, A
通讯作者：
YAGYUU, A
影响因子：
10.9
作者：
Andre, Barbara;Vercauteren, Tom;Ayache, Nicholas
通讯作者：
Ayache, Nicholas