# Groupwise Multimodal Image Registration using Joint Total Variation

arXiv: https://arxiv.org/abs/2005.02933 · HTML: https://mlsanity.com/paper/2005.02933/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 May 2020.

## Built on by (most cited first, 1 of 1)

- [Contrast-Agnostic Groupwise Registration by Robust PCA for Quantitative Cardiac MRI](https://mlsanity.com/paper/2311.01916/) (2023)

## Abstract (arXiv)

In medical imaging it is common practice to acquire a wide range of modalities (MRI, CT, PET, etc.), to highlight different structures or pathologies. As patient movement between scans or scanning session is unavoidable, registration is often an essential step before any subsequent image analysis. In this paper, we introduce a cost function based on joint total variation for such multimodal image registration. This cost function has the advantage of enabling principled, groupwise alignment of multiple images, whilst being insensitive to strong intensity non-uniformities. We evaluate our algorithm on rigidly aligning both simulated and real 3D brain scans. This validation shows robustness to strong intensity non-uniformities and low registration errors for CT/PET to MRI alignment. Our implementation is publicly available at https://github.com/brudfors/coregistration-njtv.