Energy minimization optimizes a patch-based segmentation database, reducing size by 96% with maintained accuracy and improved FFR specificity on public CCTA data.
In : Lecture Notes in Com- puter Science (including subseries Lecture Notes in Artific ial Intelligence and Lec- ture Notes in Bioinformatics)
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Learning a sparse database for patch-based medical image segmentation
Energy minimization optimizes a patch-based segmentation database, reducing size by 96% with maintained accuracy and improved FFR specificity on public CCTA data.