Background: Inter-frame image registration is a major hurdle in accurate quantification of myocardial perfusion using MRI. The registration is not standard, in that changing contrast between frames makes it difficult to register the images automatically. Methods: A multiple step approach was employed. First, a region around the heart was identified out automatically in order to focus the registration. Then we performed rigid shifts between frames with a cross correlation type of method, to obtain a coarse registration. Then we created model images from a two compartment model and an arterial input function from the RV blood pool of the images. These model images represent the uptake and washout of the contrast agent. However they do not contain any motion since the two compartment motion cannot explicitly model motion. These motion-free model images are used as reference images and each frame was registered to its associated model image. Rigid and deformable registration as implemented by ANTS. The entire process was automatic and required ~240 seconds. This registration approach was tested on the 10 provided ECG-gated rest/stress datasets. Conclusion: Rigid and deformable registration was performed on the provided datasets. The technique was found to perform better on datasets with higher signal to noise ratio and without sudden respiratory motions.
CITATION STYLE
Likhite, D., Adluru, G., & Di Bella, E. (2015). Deformable and rigid model-based image registration for quantitative cardiac perfusion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8896, pp. 41–50). Springer Verlag. https://doi.org/10.1007/978-3-319-14678-2_5
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