Abstract
This paper presents a robust method to correct for intensity differences across a series of aligned stained histological slices. The method is made up of two steps. First, for each slice, a scale-space analysis of the histogram provides a set of alternative interpretations in terms of tissue classes. Each of these interpretations can lead to a different classification of the related slice. A simple heuristics selects for each slice the most plausible interpretation. Then, an iterative procedure refines the interpretation selections across the series in order to maximize a score measuring the spatial consistency of the classifications across contiguous slices. Results are presented for a series of 121 baboon slices.
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Dauguet, J., Mangin, JF., Delzescaux, T., Frouin, V. (2004). Robust Inter-slice Intensity Normalization Using Histogram Scale-Space Analysis. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30135-6_30
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DOI: https://doi.org/10.1007/978-3-540-30135-6_30
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