Second Order Fuzzy Measure and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images

被引：0
|
作者：
Maji, Pradipta [1 ]
Kundu, Malay K. [1 ]
Chanda, Bhabatosh [2 ]
机构：
[1] Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, India
[2] Indian Stat Inst, Elect & Commun Sci Unit, Kolkata 700108, India
来源：
FUNDAMENTA INFORMATICAE | 2008年 / 88卷 / 1-2期
关键词：
Medical imaging; segmentation; thresholding; fuzzy sets; co-occurrence matrix;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
A robust thresholding technique is proposed in this paper for segmentation of brain MR images. It is based on the fuzzy thresholding techniques. Its aim is to threshold the gray level histogram of brain MR images by splitting the image histogram into multiple crisp subsets. The histogram of the given image is thresholded according to the similarity between gray levels. The similarity is assessed through a second order fuzzy measure such as fuzzy correlation, fuzzy entropy, and index of fuzziness. To calculate the second order fuzzy measure, a weighted co-occurrence matrix is presented, which extracts the local information more accurately. Two quantitative indices are introduced to determine the multiple thresholds of the given histogram. The effectiveness of the proposed algorithm, along with a comparison with standard thresholding techniques, is demonstrated on a set of brain MR images.
引用
收藏
页码：161 / 176
页数：16
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