Elastic 3D-2D Image Registration

TL;DR

This paper introduces a variational method for non-rigidly aligning 3D volumetric images with 2D projection images, enabling better integration of biological microscopy data.

Contribution

It presents a novel approach that estimates out-of-plane deformation from 2D images using out of focus blur, with a coarse-to-fine optimization strategy for computational efficiency.

Findings

Effective alignment of 3D and 2D microscopy data demonstrated

Out of plane deformation can be estimated from blur in 2D images

Method suitable for biological tissue registration

Abstract

We propose a method to non-rigidly align a three-dimensional (3D) volumetric image with a two-dimensional (2D) planar image representing a projection of the deformed volume. The application in mind comes from biological studies in which 2D intravital microscopy videos of living tissue are recorded, after which the tissue is excised and a more detailed 3D volume microscopy is performed. Coregistration of both data sets allows to combine the temporal (but 2D) information with more detailed spatial 3D information. Our approach is variational and uses a hyperelastic deformation regularization, as is appropriate for biological material. As a particular feature, the out of plane deformation is estimated based on the out of focus blur inside the 2D microscopy image. The approach becomes computationally feasible through the use of a coarse-to-fine optimization strategy and higher order optimization methods.