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2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution

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2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution

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Nombre: Beresova;Larroza;Arana ...
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dc.contributor.author Beresova, Monika es_ES
dc.contributor.author Larroza, Andrés es_ES
dc.contributor.author Arana, Estanislao es_ES
dc.contributor.author Varga, Jozsef es_ES
dc.contributor.author Balkay, Laszlo es_ES
dc.contributor.author Moratal, David es_ES
dc.date.accessioned 2020-10-22T03:31:50Z
dc.date.available 2020-10-22T03:31:50Z
dc.date.issued 2018-04 es_ES
dc.identifier.issn 0968-5243 es_ES
dc.identifier.uri http://hdl.handle.net/10251/152795
dc.description.abstract [EN] To find structural differences between brain metastases of lung and breast cancer, computing their heterogeneity parameters by means of both 2D and 3D texture analysis (TA). Patients with 58 brain metastases from breast (26) and lung cancer (32) were examined by MR imaging. Brain lesions were manually delineated by 2D ROIs on the slices of contrast-enhanced T1-weighted (CET1) images, and local binary patterns (LBP) maps were created from each region. Histogram-based (minimum, maximum, mean, standard deviation, and variance), and co-occurrence matrix-based (contrast, correlation, energy, entropy, and homogeneity) 2D, weighted average of the 2D slices, and true 3D TA were obtained on the CET1 images and LBP maps. For LBP maps and 2D TA contrast, correlation, energy, and homogeneity were identified as statistically different heterogeneity parameters (SDHPs) between lung and breast metastasis. The weighted 3D TA identified entropy as an additional SDHP. Only two texture indexes (TI) were significantly different with true 3D TA: entropy and energy. All these TIs discriminated between the two tumor types significantly by ROC analysis. For the CET1 images there was no SDHP at all by 3D TA. Our results indicate that the used textural analysis methods may help with discriminating between brain metastases of different primary tumors. es_ES
dc.description.sponsorship This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under Grant BFU2015-64380-C2-2-R, by the "Richter Gedeon Talentum Alapitvany" and by the Campus Hungary Mobility Program. Andres Larroza was funded by the Spanish Ministerio de Educacion, Cultura y Deporte (MECD) under Grant FPU12/01140. The authors also thank to the continuous help of Dr. Joaquin Gavila from Fundacion IVO es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Magnetic Resonance Materials in Physics, Biology and Medicine es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Computer-assisted es_ES
dc.subject Image processing es_ES
dc.subject Texture analysis es_ES
dc.subject Magnetic resonance imaging es_ES
dc.subject Brain neoplasms es_ES
dc.subject Metastasis es_ES
dc.subject Breast cancer es_ES
dc.subject Lung cancer es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title 2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10334-017-0653-9 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU12%2F01140/ES/FPU12%2F01140/ 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 Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Beresova, M.; Larroza, A.; Arana, E.; Varga, J.; Balkay, L.; Moratal, D. (2018). 2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution. Magnetic Resonance Materials in Physics, Biology and Medicine. 31(2):285-294. https://doi.org/10.1007/s10334-017-0653-9 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10334-017-0653-9 es_ES
dc.description.upvformatpinicio 285 es_ES
dc.description.upvformatpfin 294 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 31 es_ES
dc.description.issue 2 es_ES
dc.identifier.pmid 28939952 es_ES
dc.relation.pasarela S\379089 es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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