# 医学图像分割与配准

Medical Image Processing System Platform of R & D
Deng Chao Qiang
(Information Science and Engineering Institute,Jiangsu Polytechnic University)
Abstract: Medical image processing has being more and more widely used in modern hospitals. In this paper, these modules were included, which are image denoising, image segmentation, the image compression and the method of how to calculate the area of the focus of medical images etc. They are the base of a medical image processing system . In addition, on the basis of this design , an efficient GUI was also designed to experiment with these image processing methods. This system not only fulfilled the experimental tasks, but also provided a good base for the development of medical image processing system.
Keywords: medical image  edge detection  image segmentation  Image compression论文摘要:医学图像处理技术在现代化医院中得到了越来越广泛的应用。在本文设计医学图像处理系统中, 基本包含了图像降噪、图像分割以及病灶区域面积的计算、图像编码压缩等内容。此外,设计了一个有效的GUI,以便进行医学图像的实验。该界面的实现不但顺利完成了本设计的实验任务,而且为以后开发医学图像处理系统提供了良好的基础。

1、 前言

2、 医学图像的降噪处理方法
2.1中值滤波技术

（a）带高斯噪声图   （b）中值滤波后图     (c)带乘性噪声图像   （d）中值滤波后图

19．5855 26．3309
滤波前（图2.1（c）） 滤波后（图2.1（d））
18．6628 23．7053
2.2基于小波变换的图像降噪

（a）带高斯噪声图    (b)小波降噪后图像   （c）带乘性噪声图   (d)小波降噪后图像        图2.2图像的小波降噪

19．5855 27．4604  医学图像分割与配准
滤波前（图2.2(c)） 基于小波变换降噪后的图像（图2.2(d)）
18．6628 26．4063

3、医学图像分割处理
3.1图像边缘检测

(a) 原始图                              (b)Roberts算子法

(c)Sobel算子法                           (d)Canny算子法

3.2图像阈值法分割

3.2.1直方图分割方法

3.2.2分水岭法图像分割实现

3.2(a)原始图像                   3.2(b)分水岭法分割图像
图3.2 分割效果图

3.3计算图像病灶区域面积

如图3.3，从分割后的图像中选择结石部分图像，在该部分图像中统计中间黑色区域像素数。

[1] [2] 下一页