首页> 外文会议>The 1st International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2007) >Urine Sediment Image Segmentation based on Level Set and Mumford-Shah Model
【24h】

Urine Sediment Image Segmentation based on Level Set and Mumford-Shah Model

机译:基于水平集和Mumford-Shah模型的尿沉渣图像分割

获取原文

摘要

Because the segmentation of the target with the Level Set is based on the gradient difference of the image while the gradient difference of the blood cells in the image of the urine sediment is not obvious compared with its background. Therefore segmenting it with the Level Set is not satisfactory. The Level Set based on Mumford-Shah model in this paper depends on the comprehensive information of the image, not on the gradient of image. The model is helpful in processing the complicated and the topological structure changing object. This is very important for the segmentation of the complicated topological medical images with less obvious gradient difference. This paper intends to apply the model in the segmentation of the blood cells in the image of the urine sediment. The algorithm of this paper can eliminate the over-segment produced by the Level Set, and obtain an accurate result with fast speed. The experiment shows that this is very effective.
机译:因为具有电平集的目标的分割基于图像的梯度差,而尿沉积物图像中的血细胞的梯度差与其背景相比并不明显。因此,用水平集分割它是不令人满意的。本文基于Mumford-Shah模型的水平集取决于图像的综合信息,而不是图像的梯度。该模型有助于处理复杂和拓扑结构改变对象。这对于具有较小明显梯度差异的复杂拓扑医学图像的分割非常重要。本文旨在将模型应用于尿沉积物图像中血细胞的分段。本文的算法可以消除由电平集产生的过段,并以快速速度获得精确的结果。实验表明这是非常有效的。

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