Automatic Best Reference Slice Selection for Smooth Volume Reconstruction of a Mouse Brain From Histological Images

摘要: In this paper, we present a novel and effective method for registering histological slices of mouse brain to reconstruct 3-D volume. First, intensity variations in images are corrected through an standardization process so that values remain constant across slices. Second, the image space is transformed feature where continuous variables taken as high fidelity features accurate registration. Third, order improve quality reconstructed volume, automatic best reference slice selection algorithm developed based on iterative assessment entropy mean square error registration process. Fourth, metric evaluating volume developed. Finally, effect optimal subsequent reconstruction demonstrated.