Abstract
This article addresses the problem of histogram matching in the context of medical image processing. Such a problem occurs while comparing two images of the same object, where intensity differences are due to different acquisition conditions. This can be compensated by histogram matching or equalization. To achieve this, we based our method on windowing techniques. This allows to match implicitly continuous probability density functions, yielding more robust results than the methods issued from discrete histograms.
Chapter PDF
Similar content being viewed by others
References
Akaike, H.: An approximation to the density function. Annals of the Institute of Statistical Mathematics 6, 127–132 (1954)
Berlinet, A., Devroye, L.: A comparison of kernel density estimates. Publications de l’Institut de Statistique de l’Université de Paris 38(3), 3–59 (1994), http://jeff.cs.mcgill.ca/~luc/np.html
Bardinet, E., Ourselin, S., Malandain, G., Tandé, D., Parain, K., Ayache, N., Yelnik, J.: Three dimensional functional cartography of the human basal ganglia by registration of optical and histological serial sections. In: IEEE International Symposium on Biomedical Imaging (2002)
Castleman, K.R.: Point Operations. In: Digital Image Processing. chapter Point Operations, pp. 83–97. Prentice Hall International Editions, Englewood Cliffs (1996)
Hildebolt, C.F., Walkup, R.K., et al.: Histogram-matching and histogram-flattening contrast correction methods: a comparison. Dentomaxillofac. Radiol. 25(1), 42–47 (1996)
Lloyd, S.P.: Least squares quantization in PCM’s. Laboratories paper, Bell Telephone, Murray Hill, NJ (1957)
Malandain, G., Bardinet, E.: Fusion of autoradiographies with an mr volume using 2-d and 3-d linear transformations. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 487–498. Springer, Heidelberg (2003)
Mota, C., Gomes, J., Cavalcante, M.I.A.: Optimal Image Quantization, Perception and the Median Cut Algorithm. An. Acad. Bras. Cienc. 73(3), 303–317 (2001)
Maintz, J.B.A., Viergever, M.A.: A survey of medical image registration. Medical Image Analysis 2(1), 1–36 (1998)
Ourselin, S., Roche, A., Subsol, G., Pennec, X., Ayache, N.: Reconstructing a 3D Structure from Serial Histological Sections. Image and Vision Computing 19(1-2), 25–31 (2001)
Parzen, E.: On the estimation of a probability density function and the mode. Annals of Mathematical Statistics 33, 1065–1076 (1962)
Rosenblatt, M.: Remark on some nonparametric estimates of a density function. Annals of Mathematical Statistics 27, 832–837 (1956)
Rey, D., Stoeckel, J., Malandain, G., Ayache, N.: Using SPM to detect evolving MS lesions. In: Niessen, W.J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208, pp. 1232–1234. Springer, Heidelberg (2001)
Vanduffel, W., Tootell, R.B.H., Orban, G.A.: Attention-dependent suppression of metabolic activity in the early stages of the macaque visual system. Cerebral Cortex 10, 109–126 (2000)
Wand, M.P.: Data-Based Choice of Histogram Bin Width. The American Statistician 51(1), 59–64 (1997)
Wang, L., Lai, H.-M., Berker, G.J., Miller, D.H., Tofts, P.S.: Correction for Variations in MRI Scanner Sensitivity In Brain Studies with Histogram Matching. Magn. Reson. Med. 39, 322–327 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Malandain, G., Bardinet, E. (2003). Intensity Compensation within Series of Images. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39903-2_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-39903-2_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20464-0
Online ISBN: 978-3-540-39903-2
eBook Packages: Springer Book Archive