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. Author manuscript; available in PMC: 2019 Jun 4.
Published in final edited form as: Med Image Comput Comput Assist Interv. 2018 Sep 13;11072:464–472. doi: 10.1007/978-3-030-00931-1_53

Fig. 1.

Fig. 1

(I) Illustration of unbalanced optimal transport on a toy data set of 100 half-ellipses with different shapes (ratio of major to minor radius) and sizes (black pixel count). (II) Spatial correlations of size, shape and size + shape to VBM (pixel intensity) and UTM (mass allocation and transport costs). Positive and negative correlation indicate an increase and decrease of mass, cost, or intensity, respectively. Only UTM is able to detect size variation (highlighted box) as strongly positively correlated to mass allocation. Both UTM and VMB detect shape variation, with stronger correlations in transport cost than mass allocation in UTM. UTM identifies both change in shape and mass for the variable depending on shape plus size.