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MACRo 2015

Proceedings of the 5th International Conference on Recent Achievements in Mechatronics, Automation, Computer Sciences and Robotics

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2247-0948
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An Atlas Based Performance Evaluation of Inhomogeneity Correcting Effects

László Lefkovits
  • Department of Electrical Engineering, Faculty of Technical and Human Sciences, Sapientia University, Tg. Mureş
  • Email:
/ Szidónia Lefkovits
  • Department Informatics, Faculty of Science and Letters, “Petru Maior” University, Tg. Mureş
  • Email:
/ Mircea-Florin Vaida
  • Department of Communications, Technical University of Cluj-Napoca
Published Online: 2015-05-09 | DOI: https://doi.org/10.1515/macro-2015-0008

Abstract

In automated image processing the intensity inhomogeneity of MR images causes significant errors. In this work we analyze three algorithms with the purpose of intensity inhomogeneity correction. The well-known N3 algorithm is compared to two more recent approaches: a modified level set method, which is able to deal with intensity inhomogeneity and it is, as well, compared to an adaptation of the fuzzy c-means clustering with intensity inhomogeneity compensation techniques. We evaluate the outcomes of these three algorithms with quantitative performance measures. The measurements are done on the bias fields and on the segmented images. We consider normal brain images obtained from the Montreal Simulated Brain Database.

Keywords : MR image intensity inhomogeneity; bias field; tissue segmentation; performance metrics

References

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About the article

Received: 2015-01-12

Revised: 2015-02-25

Published Online: 2015-05-09

Published in Print: 2015-03-01



Citation Information: MACRo 2015, ISSN (Online) 2247-0948, DOI: https://doi.org/10.1515/macro-2015-0008. Export Citation

© 2015. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)

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