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