Learning to combine complementary segmentation methods for fetal and 6-month infant brain MRI segmentation

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• dc.contributor.author Piella Fenoy, Gemma
• dc.contributor.author Sanromà, Gerard
• dc.contributor.author Benkarim, Oualid M.
• dc.contributor.author Piella Fenoy, Gemma
• dc.contributor.author Lekadir, Karim, 1977-
• dc.contributor.author Hahner, Nadine
• dc.contributor.author Eixarch, Elisenda
• dc.contributor.author González Ballester, Miguel Ángel, 1973-
• dc.date.accessioned 2019-06-13T13:42:43Z
• dc.date.issued 2018
• dc.description.abstract Segmentation of brain structures during the pre-natal and early post-natal periods is the first step for subsequent analysis of brain development. Segmentation techniques can be roughly divided into two families. The first, which we denote as registration-based techniques, rely on initial estimates derived by registration to one (or several) templates. The second family, denoted as learning-based techniques, relate imaging (and spatial) features to their corresponding anatomical labels. Each approach has its own qualities and both are complementary to each other. In this paper, we explore two ensembling strategies, namely, stacking and cascading to combine the strengths of both families. We present experiments on segmentation of 6-month infant brains and a cohort of fetuses with isolated non-severe ventriculomegaly (INSVM). INSVM is diagnosed when ventricles are midly enlarged and no other anomalies are apparent. Prognosis is difficult based solely on the degree of ventricular enlargement. In order to find markers for a more reliable prognosis, we use the resulting segmentations to find abnor-malities in the cortical folding of INSVM fetuses. Segmentation results show that either combination strategy outperform all of the individual methods, thus demonstrating the capability of learning systematic combinations that lead to an overall improvement. In particular, the cascading strategy outperforms the ensembling one, the former one obtaining top 5, 7 and 13 results (out of 21 teams) in the segmentation of white matter, gray matter and cerebro-spinal fluid in the iSeg2017 MICCAI Segmentation Challenge. The resulting segmentations reveal that INSVM fetuses have a less convoluted cortex. This points to cortical folding abnormalities as potential markers of later neurodevelopmental outcomes.en
• dc.description.sponsorship The first author is co-financed by the Marie Curie FP7-PEOPLE-2012- COFUND Action, Grant agreement no: 600387. This study was partly sup345 ported by Instituto de Salud Carlos III (PI16/00861) integrados en el Plan Nacional de I+D+I y cofinanciados por el ISCIII-Subdirección General de Evaluación y el Fondo Europeo de Desarrollo Regional (FEDER) "Una manera de hacer Europa"; additionally the research leading to these results has received funding from "la Caixa" Foundation. This work is partly supported by the 350 Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502).
• dc.format.mimetype application/pdf
• dc.identifier.citation Sanroma G, Benkarim OM, Piella G, Lekadir K, Hahner N, Eixarch E, González Ballester, MA. Learning to combine complementary segmentation methods for fetal and 6-month infant brain MRI segmentation. Computerized medical imaging and graphics. 2018 Nov;69:52-9. DOI: 10.1016/j.compmedimag.2018.08.007
• dc.identifier.doi http://dx.doi.org/10.1016/j.compmedimag.2018.08.007
• dc.identifier.issn 0895-6111
• dc.identifier.uri http://hdl.handle.net/10230/41750
• dc.language.iso eng
• dc.publisher Elsevier
• dc.relation.ispartof Computerized medical imaging and graphics. 2018 Nov;69:52-9.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/600387
• dc.rights © Elsevier https://doi.org/10.1016/j.compmedimag.2018.08.007
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Fetal brain MRI segmentationen
• dc.subject.keyword Multi-atlas label fusionen
• dc.subject.keyword Stackingen
• dc.subject.keyword Cascadingen
• dc.subject.keyword Isolated non-severe ventriculomegalyen
• dc.title Learning to combine complementary segmentation methods for fetal and 6-month infant brain MRI segmentation
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/acceptedVersion