Abstract
PET images deliver functional data, whereas MRI images provide anatomical information. Merging the complementary information from these two modalities is helpful in oncology. Alignment of PET/MRI images requires the use of multi-modal registration methods. Most of existing PET/MRI registration methods have been developed for humans and few works have been performed for small animal images. We proposed an automatic tool allowing PET/MRI registration for pre-clinical study based on a two-level hierarchical approach. First, we applied a non-linear intensity transformation to the PET volume to enhance. The global deformation is modeled by an affine transformation initialized by a principal component analysis. A free-form deformation based on B-splines is then used to describe local deformations. Normalized mutual information is used as voxel-based similarity measure. To validate our method, CT images acquired simultaneously with the PET on tumor-bearing mice were used. Results showed that the proposed algorithm outperformed affine and deformable registration techniques without PET intensity transformation with an average error of 0.72 ± 0.44 mm. The optimization time was reduced by 23% due to the introduction of robust initialization. In this paper, an automatic deformable PET-MRI registration algorithm for small animals is detailed and validated.
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Notes
Experimental datasets used for the validation can be asked by email to the authors.
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Acknowledgements
This work was supported by a French Government grant managed by the French National Research Agency (ANR) under the program ‘Investissements d’Avenir’ (with reference ANR- 10-EQPX-05-01/IMAPPI Equipex) and by the Fondation de Coopération Scientifique Bourgogne Franche-Comté.
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Bricq, S., Kidane, H.L., Zavala-Bojorquez, J. et al. Automatic deformable PET/MRI registration for preclinical studies based on B-splines and non-linear intensity transformation. Med Biol Eng Comput 56, 1531–1539 (2018). https://doi.org/10.1007/s11517-018-1797-0
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DOI: https://doi.org/10.1007/s11517-018-1797-0