Per citar aquest document: http://ddd.uab.cat/record/52587
Automatic Abdominal Organ Segmentation from CT images
Campadelli, Paola (Universita degli studi di Milano. Department of Computer Science)
Casiraghi, Elena (Universita degli studi di Milano. Department of Computer Science)
Pratissoli, Stella (Universita degli studi di Milano. Department of Computer Science)
Lombardi, Gabriele (Universita degli studi di Milano. Department of Computer Science)

Data: 2009
Resum: In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. Some of the current interests are the automatic diagnosis of liver, spleen, and kidney pathologies and the 3D volume rendering of the abdominal organs. The first and fundamental step in all these studies is the automatic organs segmentation, that is still an open problem. In this paper we propose our fully automatic system that employs a hierarchical gray level based framework to segment heart, bones (i. e. ribs and spine), liver and its blood vessels, kidneys, and spleen. The overall system has been evaluated on the data of 100 patients, obtaining a good assessment both by visual inspection by three experts, and by comparing the computed results to the boundaries manually traced by experts.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Matèria: Imatges de TC abdominal ; Segmentació dels òrgans en 3D ; Anàlisi de Histograma ; Tall Gràfic ; α-expansió ; Imágenes de TC abdominal ; Segmentación de los órganos en 3D ; Análisis de Histograma ; Corte Gráfico ; α-expansión ; Abdominal CT images ; 3D organs segmentation ; Histogram analysis ; Graph cut ; α-expansion
Publicat a: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 8 n. 1 (2009) p. 1-14, ISSN 1577-5097

Adreça alternativa: http://www.raco.cat/index.php/ELCVIA/article/view/150150


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