Registration of standardized histological images in feature space

Ulaş Bağci; Li Bai

doi:10.1117/12.770219

11 March 2008 Registration of standardized histological images in feature space

Ulaş Bağci, Li Bai

Proceedings Volume 6914, Medical Imaging 2008: Image Processing; 69142V (2008) https://doi.org/10.1117/12.770219
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

In this paper, we propose three novel and important methods for the registration of histological images for 3D reconstruction. First, possible intensity variations and nonstandardness in images are corrected by an intensity standardization process which maps the image scale into a standard scale where the similar intensities correspond to similar tissues meaning. Second, 2D histological images are mapped into a feature space where continuous variables are used as high confidence image features for accurate registration. Third, we propose an automatic best reference slice selection algorithm that improves reconstruction quality based on both image entropy and mean square error of the registration process. We demonstrate that the choice of reference slice has a significant impact on registration error, standardization, feature space and entropy information. After 2D histological slices are registered through an affine transformation with respect to an automatically chosen reference, the 3D volume is reconstructed by co-registering 2D slices elastically.

Citation Download Citation

Ulaş Bağci and Li Bai "Registration of standardized histological images in feature space", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69142V (11 March 2008); https://doi.org/10.1117/12.770219

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