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Communication Dans Un Congrès Année : 2022

Optimization of a mutual shape based on the Fréchet-Nikodym metric for 3D shapes fusion

Résumé

In the field of delineation of 2D or 3D regions of interest (ROI) in medical imaging, and especially due to the development of multimodal and multiparametric image acquisition devices, the combination of segmentations of anatomical structures from different sources is interesting. It is also essential to accurately assess the variability between delineation experts or algorithms with different parameters. In this work, we propose to estimate a mutual shape defined as the optimum of a statistical criterion based on information theory. The mutual shape is computed using shape optimization tools through the computation of shape gradients. We propose to interpret the mutual shape as a sum of distances of the Fréchet family. Moreover, we extend our framework to 3D shape fusion. An example showing the interest of the combination of segmentation methods computed separately on four MRI modalities is given and we provide a synthetic example to demonstrate the difference between the mutual shape, the mean shape and the union of shapes.
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Dates et versions

hal-03697975 , version 1 (25-11-2022)

Identifiants

  • HAL Id : hal-03697975 , version 1

Citer

Stéphanie Jehan-Besson, Patrick Clarysse, Régis Clouard, Frédérique Frouin. Optimization of a mutual shape based on the Fréchet-Nikodym metric for 3D shapes fusion. International Conference on Curves and Surfaces, SMAI-SIGMA, Jun 2022, Arcachon, France. ⟨hal-03697975⟩
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