Automatic best reference slice selection for smooth volume reconstruction of a mouse brain from histological images
IEEE Transactions on Medical Imaging, 29(9), 1688–1696
Abstract
In this paper, we present a novel and effective method for registering histological slices of a mouse brain to reconstruct a 3-D volume. First, intensity variations in images are corrected through an intensity standardization process so that intensity values remain constant across slices. Second, the image space is transformed to a feature space where continuous variables are taken as high fidelity image features for accurate registration. Third, in order to improve the quality of the reconstructed volume, an automatic best reference slice selection algorithm is developed based on iterative assessment of image entropy and mean square error of the registration process. Fourth, a novel metric for evaluating the quality of the reconstructed volume is developed. Finally, the effect of optimal reference slice selection on the quality of registration and subsequent reconstruction is demonstrated.
Abstract sourceThis 2010 paper presents a method for selecting a reference slice when registering mouse-brain histology images to reconstruct a three-dimensional volume. The study evaluates how reference-slice selection affects registration and reconstruction quality.
Summary
The paper describes a method for registering histological slices of a mouse brain to reconstruct a three-dimensional volume. It standardizes image intensities across slices, transforms images into a feature space for registration, and selects a reference slice automatically using image entropy and registration mean square error. The authors also introduce a metric to evaluate reconstructed-volume quality and report demonstrating the effect of reference-slice selection on registration and reconstruction. The reported work concerns image reconstruction; the abstract does not establish clinical validation.
Cite this work
Ulaş Bagci; Li Bai (2010). Automatic best reference slice selection for smooth volume reconstruction of a mouse brain from histological images. IEEE Transactions on Medical Imaging, 29(9), 1688–1696 https://doi.org/10.1109/TMI.2010.2050594
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