SlicesMapi: An Interactive Three-Dimensional Registration Method for Serial Histological Brain Slices

Abstract

Brain slicing is a commonly used technique in brain science research. In order to study the spatial distribution of labeled information, such as specific types of neurons and neuronal circuits, it is necessary to register the brain slice images to the 3D standard brain space defined by the reference atlas. However, the registration of 2D brain slice images to a 3D reference brain atlas still faces challenges in terms of accuracy, computational throughput, and applicability. In this paper, we propose the SlicesMapi, an interactive 3D registration method for brain slice sequence. This method corrects linear and non-linear deformations in both 3D and 2D spaces by employing dual constraints from neighboring slices and corresponding reference atlas slices and guarantees precision by registering images with full resolution, which avoids the information loss of image down-sampling implemented in the deep learning based registration methods. This method was applied to deal the challenges of unknown slice angle registration and non-linear deformations between the 3D Allen Reference Atlas and slices with cytoarchitectonic or autofluorescence channels. Experimental results demonstrate Dice scores of 0.9 in major brain regions, highlighting significant advantages over existing methods. Compared with existing methods, our proposed method is expected to provide a more accurate, robust, and efficient spatial localization scheme for brain slices. Therefore, the proposed method is capable of achieving enhanced accuracy in slice image spatial positioning.

Keywords: 2D- 3D registration; Brain slice images; Histological image; Spatial localization; Spatial transcriptomic data.