• 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