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|Título:||Kidney segmentation in 3D CT images using B-Spline Explicit Active Surfaces|
|Autor(es):||Torres, Helena R.|
Fonseca, Jaime C.
Rodrigues, Nuno F.
Vilaca, Joao L.
|Palavras-chave:||B-Spline Explicit Active Surfaces|
|Revista:||Ieee International Conference on Serious Games and Applications for Health|
|Resumo(s):||In this manuscript, we propose to adapt the B-Spline Explicit Active Surfaces (BEAS) framework for semi-automatic kidney segmentation in computed tomography (CT) images. To study the best energy functional for kidney CT extraction, three different localized region-based energies were implemented within the BEAS framework, namely localized Chan-Vese, localized Yezzi, and signed localized Yezzi energies. Moreover, a novel gradient-based regularization term is proposed. The method was applied on 18 kidneys from 9 CT datasets, with different image properties. Several energy combinations were contrasted using surface-based comparison against ground truth meshes, assessing their accuracy and robustness against surface initialization. Overall, the hybrid energy functional combining the localized signed Yezzi energy with gradient-based regularization simultaneously showed the highest accuracy and the lowest sensitivity to the initialization. Volumetric analysis demonstrated the feasibility of the method from a clinical point of view, with similar reproducibility to manual observers.|
|Aparece nas coleções:||DEI - Artigos em atas de congressos internacionais|