Towards ultra-high resolution 3D reconstruction of a whole rat brain from 3D-PLI data

TL;DR

This paper presents a novel multi-scale, multi-modal registration method for ultra-high resolution 3D reconstruction of a rat brain from 3D-PLI data, enabling detailed structural connectivity analysis.

Contribution

It introduces a new feature transform-based similarity measure and a weighted regularization scheme for accurate non-rigid registration of histological brain images.

Findings

Successfully applied to 278 histological sections

Quantitative evaluation with expert landmarks

Achieved high registration accuracy

Abstract

3D reconstruction of the fiber connectivity of the rat brain at microscopic scale enables gaining detailed insight about the complex structural organization of the brain. We introduce a new method for registration and 3D reconstruction of high- and ultra-high resolution (64 $\mu$m and 1.3 $\mu$m pixel size) histological images of a Wistar rat brain acquired by 3D polarized light imaging (3D-PLI). Our method exploits multi-scale and multi-modal 3D-PLI data up to cellular resolution. We propose a new feature transform-based similarity measure and a weighted regularization scheme for accurate and robust non-rigid registration. To transform the 1.3 $\mu$m ultra-high resolution data to the reference blockface images a feature-based registration method followed by a non-rigid registration is proposed. Our approach has been successfully applied to 278 histological sections of a rat brain and the performance has been quantitatively evaluated using manually placed landmarks by an expert.