Cui Jinli, Wang Yadong, Wang Ke
Department of Radiology, Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun 130000, Jilin, China.
Department of Computer Science and Technology, Changchun University of Technology, Changchun 130000, Jilin, China.
Emerg Med Int. 2022 Jun 15;2022:6711043. doi: 10.1155/2022/6711043. eCollection 2022.
Mean-shift originally refers to the mean vector of the offset. The algorithm idea is to assume that the data sets of different clusters conform to different probability density distributions, and the area with high sample density corresponds to the center of the cluster. With the wide application of hospital information system, especially the popularity of the meanshift algorithm in the outpatient system, it has greatly improved the efficiency of medical staff. Medical imaging refers to the technology and process of obtaining internal tissue images of the human body or a certain part of the human body in a noninvasive manner for medical treatment or medical research. It contains the following two relatively independent research directions: medical imaging system and medical image processing. In this paper, we expect to improve the mining ability of medical image information with the help of the meanshift algorithm based on the key technology of the medical image intelligent mining algorithm. This paper proposes a method to enhance image feature extraction and data mining and how to apply relevant analysis rules for mining. Applying this integrated algorithm to extract simplified rules is more beneficial to people's understanding than the raw data and helps doctors quickly understand the patient's condition.
均值漂移最初指的是偏移量的均值向量。该算法的思想是假设不同聚类的数据集符合不同的概率密度分布,样本密度高的区域对应聚类的中心。随着医院信息系统的广泛应用,尤其是均值漂移算法在门诊系统中的普及,极大地提高了医务人员的工作效率。医学成像指的是以非侵入方式获取人体内部组织图像或人体某一部位图像以用于医疗或医学研究的技术和过程。它包含以下两个相对独立的研究方向:医学成像系统和医学图像处理。在本文中,我们期望借助基于医学图像智能挖掘算法关键技术的均值漂移算法来提高医学图像信息的挖掘能力。本文提出了一种增强图像特征提取和数据挖掘以及如何应用相关分析规则进行挖掘的方法。应用这种集成算法提取简化规则比原始数据更有利于人们理解,有助于医生快速了解患者病情。