首页> 外文会议>Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing; Lecture Notes in Artificial Intelligence; 4482 >A Study: Segmentation of Lateral Ventricles in Brain MRI Using Fuzzy C-Means Clustering with Gaussian Smoothing
【24h】

A Study: Segmentation of Lateral Ventricles in Brain MRI Using Fuzzy C-Means Clustering with Gaussian Smoothing

机译:研究:使用高斯平滑的模糊C均值聚类在脑MRI中对侧脑室进行分割

获取原文
获取原文并翻译 | 示例

摘要

This paper demonstrates a study on lateral ventricles segmentation in brain Magnetic Resonance Imaging (MRI). The method applies Gaussian smoothed image data as additional features into the feature space of Fuzzy C-Means (FCM) algorithm. With the aid of the smoothing effect from Gaussian filters, FCM is able to segment lateral ventricular compartments by reducing inappropriate clustering caused by noise and inhomogeneous intensity distribution. The results demonstrate both noise insensitivity and more homogeneous clustering.
机译:本文证明了在脑磁共振成像(MRI)中对侧脑室分割的研究。该方法将高斯平滑图像数据作为附加特征应用到模糊C均值(FCM)算法的特征空间中。借助高斯滤波器的平滑效果,FCM能够通过减少由噪声和不均匀强度分布引起的不适当聚类来分割心室侧面。结果表明噪声不敏感和更均匀的群集。

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