摘要随着数字医疗技术的快速发展，医学图像处理在医疗领域的作用变得越来越重要。传统的医学方法主要是依靠医生的个人经验来分析医学图像，从而进行病情诊断，但这种方法已难以适应时代的需求。面对海量的医学图像，需要建立有效的医学图像分类与检索系统。本文通过研究医学图像纹理分析方法，实现了四种有效的纹理特征提取算法，而这四种算法将为建立医学图像分类与检索系统提供必要的基础。

本文主要介绍了图像纹理特征提取的四大类方法，统计法、频谱法、模型法和结构法，并对四大类提取方法作了总结和对比。在此基础上，选取了常用的四种方法，灰度共生矩阵、Tamura纹理分析、局部二值模式和Gabor滤波法来实现医学图像纹理的提取。文中详细的介绍了这四种算法的原理、实现和测试结果。最后，对本文所做的工作进行了系统的总结，展望了纹理特征提取技术在图像分类与检索领域中的应用前景。84798

毕业论文关键词：纹理特征提取；医学图像；统计法；频谱法

Abstract With the rapid development of digital medical technology, medical image processing is becoming more and more important in the medical field。 Traditional medical methods mainly rely on the doctor's personal experience to analyze the medical image, so as to diagnose the disease, but this method has been difficult to adapt to the needs of the times。 Faced with massive medical image, effective medical image classification and retrieval system is needed。 Based on the research of medical image texture analysis method, the realization of the four kinds of texture feature extraction algorithm effectively, and the four kinds of algorithms for medical image classification and retrieval system to provide the necessary foundation。

This article mainly introduced the four broad categories of image texture feature extraction method, statistical method, spectral method, model method and structural method, and the four categories of extraction method summarized and compared。 On this basis, the selection of the commonly used four methods of gray level co-occurrence matrix texture analysis, Tamura, local binary pattern and Gabor filtering method to realize the medical image texture extraction。 This paper introduced the principle of the four algorithms, implementation and test results。 Finally, the paper summarized the work of the system, and the texture feature extraction technology was put forward the application prospect in the field of image classification and retrieval。

Keywords: texture feature extraction; medical image; statistical method; spectral method

 目  录

第一章 绪论 1

1。1 研究背景和意义 1

1。3 图像分类研究的发展与现状 2

1。4 论文内容及章节排版 3

第二章 纹理的描述与分析 4

2。1 引言 4

2。2 纹理特征与性质 4

2。3 医学图像的特点 5

2。4 纹理特征的提取方法 5

2。4。1 概述 5

2。4。2 统计法 6

2。4。3 频谱法 6

2。4。5 结构法 8

第三章 基于统计法的纹理特征提取方法 9

3。1 灰度共生矩阵法 9

3。1。1 原理