DOI QR코드

DOI QR Code

Contrast Enhancement for Segmentation of Hippocampus on Brain MR Images

  • Received : 2012.02.07
  • Accepted : 2012.08.02
  • Published : 2012.12.31

Abstract

An image segmentation result depends on pre-processing steps such as contrast enhancement, edge detection, and smooth filtering etc. Especially medical images are low contrast and contain some noises. Therefore, the contrast enhancement and noise removal techniques are required in the pre-processing. In this study, we present an extension by a novel histogram equalization in which both local and global contrast is enhanced using neighborhood metrics. When checking neighborhood information, filters can simultaneously improve image quality. Most important is that original image information can be used for both global brightness preserving and local contrast enhancement, and image quality improvement filtering. Our experiments confirmed that the proposed method is more effective than other similar techniques reported previously.

Keywords

References

  1. H. Wang, J.W. Suh, S. Das, M. Altinay, J. Pluta, and P. Yushkevich, "Hippocampus Segmentation using a Stable Maximum Likelihood Classifier Ensemble Algorithm," Biomedical Imaging: From Nano to Macro, IEEE International Symposium, pp. 2036-2040, 2011.
  2. Yan Xia, Keith Bettinger, Lin Shen, and Allan L. Reiss., "Automatic Segmentation of the Caudate Nucleus From Human Brain MR Images," IEEE Transactions on Medical Imaging, Vol. 26, No. 4, pp. 509-517, 2007. https://doi.org/10.1109/TMI.2006.891481
  3. J. Barnes, J. Foster, R.G. Boyes, T. Pepple, E.K. Moore, J.M. Schott, C. Frost, R.I. Scahill, and N.C. Fox., "A Comparison of Methods for the Automated Calculation of Volumes and Atrophy Rates in the Hippocampus," Neuro- Image, Vol. 40, No. 4, pp. 1655-1671, 2008.
  4. Killiany. R.J., Hyman, N., and Gomez-Isla. T., "MRI Measures of Entorhinal Cortex vs Hippocampus in Preclinical AD," Neurology, Vol. 58, No. 8, pp. 1188-1196, 2002 https://doi.org/10.1212/WNL.58.8.1188
  5. Xu. Y., Jack Jr. C.R., O'Brien. P.C., Kokmen. E., Smith. G.E., Ivnik. R.J., Boeve. B.F., Tangalos. R.G., and Petersen. R.C., "Usefulness of MRI Measures of Entorhinal Cortex Versus Hippocampus in AD," Neurology, Vol. 54, No. 9, pp. 1760-1767, 2000. https://doi.org/10.1212/WNL.54.9.1760
  6. Sengee. N., Sengee. A., and Choi, H-K, "Image Contrast Enhancement using Bi-Histogram Equalization with Neighborhood Metrics," IEEE Transactions on Consumer Electronics, Vol. 56, No. 4, pp. 2727-2734, 2010. https://doi.org/10.1109/TCE.2010.5681162
  7. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice-Hall, New Jersey, 2002.
  8. Yeong-Taeg Kim, "Contrast Enhancement using Brightness Preserving Bi-histogram Equalization," IEEE Transactions on Consumer Electronics, Vol. 43, No. 1, pp. 1-8, 1997. https://doi.org/10.1109/30.580378
  9. Y. Wang, Q. Chen, and B. Zhang, "Image Enhancement Based on Equal Area Dualistic Sub-image Histogram Equalization Method," IEEE Transactions on Consumer Electronics, Vol. 45, No. 1, pp. 65-75, 1999.
  10. S.D. Chen and A.R Ramli, "Minimum Mean Brightness Error Bi-histogram Equalization in Contrast Enhancement," IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, pp. 1310-1319, 2003. https://doi.org/10.1109/TCE.2003.1261234
  11. S.D. Chen and A.R Ramli, "Contrast Enhancement using Recursive Mean-separate Histogram Equalization for Scalable Brightness Preservation," IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, pp. 1301-1309, 2003. https://doi.org/10.1109/TCE.2003.1261233
  12. K.S. Sim, C.P. Tso, and Y.Y. Tan, "Recursive Sub-image Histogram Equalization Applied to Gray Scale Images," Pattern Recognition Letters, Vol. 28, No. 10, pp. 1209- 1221, 2007. https://doi.org/10.1016/j.patrec.2007.02.003
  13. D. Menotti, L. Najman, J. Facon, and A.D.A. Araujo, "Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving," IEEE Transactions on Consumer Electronics, Vol. 53, No. 3, pp. 1186-1194, 2007. https://doi.org/10.1109/TCE.2007.4341603
  14. A.A. Wadud, M.H. Kabir, M.A.A. Dewan, and O. Chae, "A Dynamic Histogram Equalization for Image Contrast Enhancement," IEEE Transactions on Consumer Electronics, Vol. 53, No. 2, pp. 1-2, 2007. https://doi.org/10.1109/TCE.2007.339492
  15. H. Ibrahim and N.S.P. Kong, "Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement," IEEE Transactions on Consumer Electronics, Vol. 53, No. 4, pp. 1752-1758, 2007. https://doi.org/10.1109/TCE.2007.4429280
  16. S.M. Pizer, E.P. Amburn, J.D. Austin, R. Cromartie, A. Geselowwitz, T. Greer, B.H. Romeny, J. B. Zimmerman, and K. Zuiderveld, "Adaptive Histogram Equalization and Its Variations," Computer Vision, Graphics, and Image Processing, Vol. 39, No. 3, pp. 355-368, 1987. https://doi.org/10.1016/S0734-189X(87)80186-X
  17. C. Wang and Z. Ye, "Brightness Preserving Histogram Equalization with Maximum Entropy: A Variational Perspective," IEEE Transactions on Consumer Electronics, Vol. 51, No. 4, pp. 1326-1334, 2005. https://doi.org/10.1109/TCE.2005.1561863
  18. M. Eramian and D. Mould, "Histogram Equalization using Neighborhood Metrics," Proceedings of Computer and Robot Vision, the 2nd Canadian Conference on IEEE CNF, pp. 397-404, 2005.
  19. Sengee. N and Choi. H-K, "Contrast Enhancement using Histogram Equalization with a New Neighborhood Metrics," Journal of Korea Multimedia Society, Vol. 11, No. 6, pp. 737-745, 2008.

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