基于排序和多视图学习的医学媒体数据区域图像检索

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI:10.1109/ACII.2015.7344672

Wei Huang, Shuru Zeng, Guang Chen

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引用次数: 3

摘要

本文首次提出了一种基于医学多模态数据的基于区域的图像检索方法，该方法采用排序和多视图学习技术。推导了代理排名评价测度，并基于代理测度进行梯度上升直接优化，实现排名和学习。构建了由1000例真实患者数据组成的数据库，并采用了几种流行的模式识别方法进行性能评价。从统计学的角度来看，我们的新方法在医学图像检索的应用上优于其他方法。

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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Region-based image retrieval based on medical media data using ranking and multi-view learning

In this study, a novel region-based image retrieval approach via ranking and multi-view learning techniques is introduced for the first time based on medical multi-modality data. A surrogate ranking evaluation measure is derived, and direct optimization via gradient ascent is carried out based on the surrogate measure to realize ranking and learning. A database composed of 1000 real patients data is constructed and several popular pattern recognition methods are implemented for performance evaluation compared with ours. It is suggested that our new method is superior to others in this medical image retrieval utilization from the statistical point of view.

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来源期刊

2015 International Conference on Affective Computing and Intelligent Interaction (ACII)

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