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Fully automatic 3D reconstruction of histological images

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2 Author(s)
Ulas Bagci ; Collaborative Medical Image Analysis on Grid (CMIAG), The University of Nottingham, United Kingdom ; Li Bai

In this paper, we propose a computational framework for 3D volume reconstruction from 2D histological slices using registration algorithms in feature space. To improve the quality of reconstructed 3D volume, first, intensity variations in images are corrected by an in tensity standardization process which maps image intensity scale to a standard scale where similar intensities correspond to similar tissues. Second, a subvolume approach is proposed for 3D reconstruction by dividing standardized slices into groups. Third, in order to improve the quality of the reconstruction process, an automatic best reference slice selection algorithm is developed based on an iterative assessment of image entropy and mean square error of the registration process. Finally, we demonstrate that the choice of the reference slice has a significant impact on registration quality and subsequent 3D reconstruction.

Published in:

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro

Date of Conference:

14-17 May 2008