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A Method for Liver Segmentation on Computed Tomography Images in Venous Phase Suitable for Real Environments

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A Method for Liver Segmentation on Computed Tomography Images in Venous Phase Suitable for Real Environments

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dc.contributor.author López-Mir, Fernando es_ES
dc.contributor.author González Pérez, Pablo es_ES
dc.contributor.author Naranjo Ornedo, Valeriana es_ES
dc.contributor.author Pareja, Eugenia es_ES
dc.contributor.author Morales, Sandra es_ES
dc.contributor.author Solaz-Minguez, Jaime es_ES
dc.date.accessioned 2016-11-18T11:10:18Z
dc.date.available 2016-11-18T11:10:18Z
dc.date.issued 2015-10
dc.identifier.issn 2156-7018
dc.identifier.uri http://hdl.handle.net/10251/74339
dc.description.abstract Nowadays, different methods are being published for the segmentation of the liver but, in general, most of them are not suitable for clinical practice due to several inconveniences as high computational cost, excessive user dependence or low accuracy. The purpose of this paper is to present the performance and validation of a liver segmentation method in computed tomography images (contrast venous phase) where automation, easy user interaction, and low computational cost (besides the required accuracy for clinical purposes) have been taken into account. Firstly, an adaptive filter based on intrinsic parameters of the liver is applied to reduce noise but preserving external liver gradients. In a second step, from a seed or a group of them, voxels with similar intensities are included in an initial 3D mask. Finally, thanks to the combination of morphological operators in different orientations, several non-liver structures (cava vein, ribs, stomach or heart) are removed and the final 3D liver mask is obtained. Thirty public datasets have been used to estimate the accuracy of the proposed algorithm, twenty for training the method and ten for testing it. An average Jaccard index of 0.91 (±0.03), a Hausdorff distance of 26.68 (±10.42) mm, and a runtime of 0.25 seconds per slice, state a promising efficiency and efficacy in the test datasets. To our knowledge, liver segmentation methods in the state of the art are achieving high accuracy at the expense of requiring an exhaustive training stage and so much clinician interaction time in different steps of the process. In this paper, a method based on intensity properties is carried out with a high grade of automatism, an easy user interaction and a low computational cost. The results obtained for different patients state a low variance and a good accuracy in most images, thus the robustness of the method is demonstrated. es_ES
dc.description.sponsorship Thanks to the Hospital Clinica Benidorm (HCB) for funding this project. This work has been supported by the Centro para el Desarrollo Tecnologico Industrial (CDTI) under the project ONCOTIC (IDI-20101153), partially by the Ministry of Education and Science Spain (TIN2010-20999-004-01). en_EN
dc.language Inglés es_ES
dc.publisher American Scientific Publishers es_ES
dc.relation.ispartof Journal of Medical Imaging and Health Informatics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject COMPUTER TOMOGRAPHY es_ES
dc.subject HEPATIC PLANNING es_ES
dc.subject INTENSITY MODEL ALGORITHM es_ES
dc.subject LIVER SEGMENTATION es_ES
dc.subject MATHEMATICAL MORPHOLOGY es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.title A Method for Liver Segmentation on Computed Tomography Images in Venous Phase Suitable for Real Environments es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1166/jmihi.2015.1509
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//IDI-20101153/ES/TERAPIAS ASISTIVAS COLABORATIVAS PARA EL TRATAMIENTO ONCOLÓGICO MEDIANTE EL USO DE TECNOLOGÍAS TIC - ONCOTIC/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2010-20999-C04-01/ES/MODELIZACION BIOMECANICA DE TEJIDOS APLICADO A CIRUGIA ASISTIDA POR ORDENADOR/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Telecomunicación - Escola Tècnica Superior d'Enginyers de Telecomunicació es_ES
dc.description.bibliographicCitation López-Mir, F.; González Pérez, P.; Naranjo Ornedo, V.; Pareja, E.; Morales, S.; Solaz-Minguez, J. (2015). A Method for Liver Segmentation on Computed Tomography Images in Venous Phase Suitable for Real Environments. Journal of Medical Imaging and Health Informatics. 5(6):1208-1216. https://doi.org/10.1166/jmihi.2015.1509 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1166/jmihi.2015.1509 es_ES
dc.description.upvformatpinicio 1208 es_ES
dc.description.upvformatpfin 1216 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 5 es_ES
dc.description.issue 6 es_ES
dc.relation.senia 293186 es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Hospital Clinica Benidorm es_ES


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