Presentation
17 March 2020 Joint intensity fusion with normalized cross-correlation metric for cross-modality MRI synthesis (Conference Presentation)
Author Affiliations +
Abstract
In this work, we extend the joint-intensity fusion (JIF) algorithm to use normalized cross-correlation (NCC) as the weighting metric for use in the context of cross-modality MRI synthesis, rather than sum squared intensity differences (SSD). We evaluate our method using the Kirby dataset, by synthesizing a representative FLAIR from a target subject’s T1w image. The accuracy of the synthetic FLAIR can be confirmed using the FLAIR taken for the target subject during the imaging session. For each subject in the dataset, using NCC with JIF results in a 51% lower mean absolute error than using SSD.
Conference Presentation
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Kathryn Ufford, Simon Vandekar, and Ipek Oguz "Joint intensity fusion with normalized cross-correlation metric for cross-modality MRI synthesis (Conference Presentation)", Proc. SPIE 11313, Medical Imaging 2020: Image Processing, 1131304 (17 March 2020); https://doi.org/10.1117/12.2550009
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KEYWORDS
Magnetic resonance imaging

Image fusion

Detection and tracking algorithms

Image segmentation

Image processing algorithms and systems

Medical imaging

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