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Automatic segmentation of the spine by means of a probabilistic atlas with a special focus on ribs suppression

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Automatic segmentation of the spine by means of a probabilistic atlas with a special focus on ribs suppression

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dc.contributor.author Ruiz-España, Silvia es_ES
dc.contributor.author Domingo, Juan es_ES
dc.contributor.author Díaz-Parra, Antonio es_ES
dc.contributor.author Dura, Esther es_ES
dc.contributor.author D'Ocon-Alcaniz, Victor es_ES
dc.contributor.author Arana, Estanislao es_ES
dc.contributor.author Moratal, David es_ES
dc.date.accessioned 2020-10-27T04:32:29Z
dc.date.available 2020-10-27T04:32:29Z
dc.date.issued 2017-09 es_ES
dc.identifier.issn 0094-2405 es_ES
dc.identifier.uri http://hdl.handle.net/10251/153235
dc.description.abstract [EN] Purpose: The development of automatic and reliable algorithms for the detection and segmentation of the vertebrae are of great importance prior to any diagnostic task. However, an important problem found to accurately segment the vertebrae is the presence of the ribs in the thoracic region. To overcome this problem, a probabilistic atlas of the spine has been developed dealing with the proximity of other structures, with a special focus on ribs suppression. Methods: The data sets used consist of Computed Tomography images corresponding to 21 patients suffering from spinal metastases. Two methods have been combined to obtain the final result: firstly, an initial segmentation is performed using a fully automatic level-set method; secondly, to refine the initial segmentation, a 3D volume indicating the probability of each voxel of belonging to the spine has been developed. In this way, a probability map is generated and deformed to be adapted to each testing case. Results: To validate the improvement obtained after applying the atlas, the Dice coefficient (DSC), the Hausdorff distance (HD), and the mean surface-to-surface distance (MSD) were used. The results showed up an average of 10 mm of improvement accuracy in terms of HD, obtaining an overall final average of 15.51 2.74 mm. Also, a global value of 91.01 3.18% in terms of DSC and a MSD of 0.66 0.25 mm were obtained. The major improvement using the atlas was achieved in the thoracic region, as ribs were almost perfectly suppressed. Conclusion: The study demonstrated that the atlas is able to detect and appropriately eliminate the ribs while improving the segmentation accuracy. es_ES
dc.description.sponsorship The authors thank the financial support of the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under Grants TEC2012-33778 and BFU2015-64380-C2-2-R (D.M.) and DPI2013-4572-R (J.D., E.D.) es_ES
dc.language Inglés es_ES
dc.publisher John Wiley & Sons es_ES
dc.relation.ispartof Medical Physics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Computed tomography es_ES
dc.subject Probabilistic atlas es_ES
dc.subject Ribs suppression es_ES
dc.subject Vertebral segmentation es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Automatic segmentation of the spine by means of a probabilistic atlas with a special focus on ribs suppression es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1002/mp.12431 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//DPI2013-45742-R/ES/DESARROLLO Y VALIDACION DE UN MODELO FARMACOCINETICO BASADO EN CORREGISTRO MAS SEGMENTACION PRECISAS DE IMAGENES 4D DE RESONANCIA MAGNETICA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TEC2012-33778/ES/CARACTERIZACION CUANTITATIVA DE LA METASTASIS VERTEBRAL MEDIANTE ANALISIS DE IMAGEN DE TC Y MODELADO POR ELEMENTOS FINITOS PARA LA DETERMINACION DEL RIESGO DE FRACTURA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//BFU2015-64380-C2-2-R/ES/ANALISIS DE TEXTURAS EN IMAGEN CEREBRAL MULTIMODAL POR RESONANCIA MAGNETICA PARA UNA DETECCION TEMPRANA DE ALTERACIONES EN LA RED Y BIOMARCADORES DE ENFERMEDAD/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Ruiz-España, S.; Domingo, J.; Díaz-Parra, A.; Dura, E.; D'ocon-Alcaniz, V.; Arana, E.; Moratal, D. (2017). Automatic segmentation of the spine by means of a probabilistic atlas with a special focus on ribs suppression. Medical Physics. 44(9):4695-4707. https://doi.org/10.1002/mp.12431 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1002/mp.12431 es_ES
dc.description.upvformatpinicio 4695 es_ES
dc.description.upvformatpfin 4707 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 44 es_ES
dc.description.issue 9 es_ES
dc.identifier.pmid 28650514 es_ES
dc.relation.pasarela S\352904 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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