【24h】

Optimized Clustering Method for CT Brain Image Segmentation

机译:CT脑图像分割的优化聚类方法

获取原文

摘要

Though image segmentation is a fundamental task in image analysis; it plays a vital role in the area of image processing. Its value increases in case of medical diagnostics through medical images like X-ray, PET, CT and MRI. In this paper, an attempt is taken to analyse a CT brain image. It has been segmented for a particular patch in the brain CT image that may be one of the tumours in the brain. The purpose of segmentation is to partition an image into meaningful regions with respect to a particular application. Image segmentation is a method of separating the image from the background, read the contents and isolating it. In this paper both the concept of clustering and thresholding technique with edge based segmentation methods like sobel, prewitt edge detectors is applied. Then the result is optimized using GA for efficient minimization of the objective function and for improved classification of clusters. Further the segmented result is passed through a Gaussian filter to obtain a smoothed image.
机译:虽然图像分割是图像分析中的基本任务;它在图像处理领域起着至关重要的作用。由于X射线,PET,CT和MRI等医学图像,它的价值随着医学诊断而增加。在本文中,试图分析CT脑图像。它已经为脑CT图像中的特定贴剂分段,其可以是大脑中的肿瘤之一。分割的目的是在特定应用程序中将图像分为有意义的区域。图像分割是一种将图像与背景分离的方法,读取内容并隔离它。在本文中,应用了与Sobel,PREWITT边缘检测器等边缘的分段方法的聚类和阈值技术的概念。然后,使用GA优化结果,以实现目标函数的有效最小化和改进的集群分类。此外,分段结果通过高斯滤波器以获得平滑图像。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号