Groupwise Multimodal Image Registration using Joint Total Variation

• URL: http://arxiv.org/abs/2005.02933v1
• Date: Wed, 6 May 2020 16:11:32 GMT
• Title: Groupwise Multimodal Image Registration using Joint Total Variation
• Authors: Mikael Brudfors, Ya\"el Balbastre, John Ashburner
• Abstract summary: We introduce a cost function based on joint total variation for such multimodal image registration. We evaluate our algorithm on rigidly aligning both simulated and real 3D brain scans.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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