INSPIRE: Intensity and spatial information-based deformable image registration

TL;DR

INSPIRE is a novel deformable image registration method that combines intensity and spatial information with elastic B-splines, offering high accuracy, robustness, and efficiency across diverse 2D and 3D medical imaging datasets.

Contribution

The paper introduces INSPIRE, a new registration framework integrating intensity and spatial measures with inverse inconsistency penalization for symmetric, efficient, and accurate registration.

Findings

Outperforms existing methods on retinal image datasets.

Achieves top performance on 3D brain MRI benchmarks.

Provides stable and robust registration results.

Abstract

We present INSPIRE, a top-performing general-purpose method for deformable image registration. INSPIRE brings distance measures which combine intensity and spatial information into an elastic B-splines-based transformation model and incorporates an inverse inconsistency penalization supporting symmetric registration performance. We introduce several theoretical and algorithmic solutions which provide high computational efficiency and thereby applicability of the proposed framework in a wide range of real scenarios. We show that INSPIRE delivers highly accurate, as well as stable and robust registration results. We evaluate the method on a 2D dataset created from retinal images, characterized by presence of networks of thin structures. Here INSPIRE exhibits excellent performance, substantially outperforming the widely used reference methods. {We also evaluate INSPIRE on the Fundus Image Registration Dataset (FIRE), which consists of 134 pairs of separately acquired retinal images. INSPIRE exhibits excellent performance on the FIRE dataset, substantially outperforming several domain-specific methods.} We also evaluate the method on four benchmark datasets of 3D magnetic resonance images of brains, for a total of 2088 pairwise registrations. A comparison with 17 other state-of-the-art methods reveals that INSPIRE provides the best overall performance. Code is available at http://github.com/MIDA-group/inspire