DocumentCode :
3565440
Title :
Comparison of image registration similarity measures for an abdominal organ segmentation framework
Author :
Golkar, Ehsan ; Abd Rahni, Ashrani A. ; Sulaiman, Riza
Author_Institution :
Univ. Kebangsaan Malaysia, Bangi, Malaysia
fYear :
2014
Firstpage :
442
Lastpage :
445
Abstract :
Automated segmentation is a primary step in medical diagnosis applications. This paper presents an image segmentation propagation method via image registration. Therefore, segmentation propagation accuracy depends on the accuracy of image registration. Three similarity measures were considered, namely Sum of Squared (Intensity) Differences (SSD), Mutual Information (MI) and Cross Correlation (CC) and their results were compared to each other. The results shows that there are slight differences between the use of these different similarity measures, however, the results are similar in the evaluation using MR images.
Keywords :
biological organs; biomedical MRI; correlation methods; image matching; image registration; image segmentation; information theory; medical image processing; CC measure; MI measure; MR image; SSD measure; abdominal organ segmentation framework; automated segmentation; cross correlation; image registration accuracy dependence; image registration similarity measure; image segmentation propagation method; intensity difference; medical diagnosis application; mutual information; segmentation propagation accuracy; sum of squared difference; Biomedical measurement; Heart; Image registration; Image segmentation; Kidney; Liver;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Sciences (IECBES), 2014 IEEE Conference on
Type :
conf
DOI :
10.1109/IECBES.2014.7047538
Filename :
7047538
Link To Document :
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