Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/53097

TítuloKidney segmentation in 3D CT images using B-Spline Explicit Active Surfaces
Autor(es)Torres, Helena R.
Oliveira, Bruno
Queiros, Sandro
Morais, Pedro
Fonseca, Jaime C.
D'hooge, Jan
Rodrigues, Nuno F.
Vilaca, Joao L.
Palavras-chaveB-Spline Explicit Active Surfaces
Computed Tomography
Kidney segmentation
Surface analysis
Volumetric analysis
Data2016
EditoraIEEE
RevistaIeee 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.
TipoconferencePaper
URIhttp://hdl.handle.net/1822/53097
ISBN978-150902209-0
DOI10.1109/SeGAH.2016.7586276
ISSN2330-5649
Arbitragem científicayes
AcessoopenAccess
Aparece nas coleções:DEI - Artigos em atas de congressos internacionais

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