More than pretty images – Towards confidence bounds on segmentation thresholds
Résumé
We present an approach to assess the uncertainty associated to classifying voxels into different material phases. The approach consists in a spectral deconvolution of the grey-level histogram using a Gaussian mixture approach, followed by an iterative classification procedure based on the occurrence frequency. As phase attributions become increasingly more uncertain as iterations proceed, confidence bounds on the final segmentation are naturally obtained.
Origine : Fichiers produits par l'(les) auteur(s)
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