KL Distance Weighted CV Model Based on Local Neighborhood Information

LIU Yan-jie; LU Zhen-tai; FENG Qian-jin; CHEN Wu-fan

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KL Distance Weighted CV Model Based on Local Neighborhood Information

更新时间：2025-07-16

- KL Distance Weighted CV Model Based on Local Neighborhood Information
- Acta Electronica Sinica Vol. 39, Issue 6, Pages: 1447-1451(2011)
- 作者机构：
  
  南方医科大学医学图像处理重点实验室,广东,广州,510515
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP319
- Published：2011
- 稿件说明：
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LIU Yan-jie, LU Zhen-tai, FENG Qian-jin, et al. KL Distance Weighted CV Model Based on Local Neighborhood Information[J]. Acta Electronica Sinica, 2011, 39(6): 1447-1451.
DOI：

LIU Yan-jie, LU Zhen-tai, FENG Qian-jin, et al. KL Distance Weighted CV Model Based on Local Neighborhood Information[J]. Acta Electronica Sinica, 2011, 39(6): 1447-1451. DOI：

摘要

本文提出了基于Kullback-Leibler(KL)距离加权和局部邻域信息的Chen-Vese(CV)模型.引入KL距离作为内外部局部区域能量的权值系数;计算曲线附近点的局部邻域能量之和作为模型的内部能量

从而提高对边缘的检测性能

并降低区域内灰度不均匀等因素对曲线进化的影响.验证实验采用大量实际临床数据

结果表明该算法能准确地分割医学图像

且能量函数有较好的收敛性.

Abstract

We propose an improved model that changes those parameters by Kullback-Leibler(KL) distance and global region by local neighborhood near the curve.Validation is implemented by experiments on mass clinical images.Take manual segmentation by a medical expert as a standard

we show that the new model improves the segmentation results compared to traditional CV model.The function has better convergence speed and stability.

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