基于roi的医学领域知识引导挖掘方法

Haiwei Pan, Qilong Han, Guisheng Yin, Wei Zhang, Jianzhong Li, Jun Ni
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引用次数: 5

摘要

图像挖掘是一个日益发展的研究热点,它不仅仅是数据挖掘在图像领域的延伸,而是一项跨学科的努力。很少有人系统地研究过这个领域。医学图像中关联规则的挖掘是特定领域应用图像挖掘的重要组成部分,因为有几个技术方面的问题使得该问题具有挑战性。本文首先将领域知识引入到感兴趣点提取算法和感兴趣点聚类算法中,然后扩展了医学图像中基于感兴趣点和图像的关联规则的概念,提出了两种从医学图像中发现频繁项集和挖掘感兴趣关联规则的算法。我们的程序获得了一些有趣的结果,我们相信我们遇到的许多问题很可能出现在其他领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A ROI-Based Mining Method with Medical Domain Knowledge Guidance
Image mining is a growing research focus and is more than just an extension of data mining to image domain but an interdisciplinary endeavor. Very few people have systematically investigated this field. Mining association rules in medical images is an important part in domain- specific application image mining because there are several technical aspects which make this problem challenging. In this paper, we firstly incorporate the domain knowledge into the ROI extraction algorithm and ROI clustering algorithm, then we extend the concept of association rule based on ROI and image in medical images, and propose two algorithms to discover frequent item-sets and mine interesting association rules from medical images. Some interesting results are obtained by our program and we believe many of the problems we come across are likely to appear in other domains.
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