Automatic segmentation of the fetal cerebellum on ultrasound volumes, using a 3D statistical shape model.
Previous work has shown that the segmentation of anatomical structures on 3D ultrasound data sets provides an important tool for the assessment of the fetal health. In this work, we present an algorithm based on a 3D statistical shape model to segment the fetal cerebellum on 3D ultrasound volumes. T...
| Published in: | Medical & Biological Engineering & Computing Vol. 51; no. 9; pp. 1021 - 1031 |
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| Main Authors: | , , , , , |
| Format: | research Journal Article |
| Published: |
Springer Nature
Sep2013
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104085635&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104085635 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2013 vid: 51 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104085635 NLM23686392 2012212866 10.1007/s11517-013-1082-1 NLM23686392 104085635 ppf: 1021 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Automatic segmentation of the fetal cerebellum on ultrasound volumes, using a 3D statistical shape model. aug: au: Gutiérrez-Becker, Benjamín Arámbula Cosío, Fernando Guzmán Huerta, Mario E Benavides-Serralde, Jesús Andrés Camargo-Marín, Lisbeth Medina Bañuelos, Verónica affil: Biomedical Imaging Lab., Center of Applied Science and Technological Development, Universidad Nacional Autónoma de México (UNAM), 04510, Mexico, D.F., Mexico, ingutbecker@gmail.com. sug: subj: Cerebellum Embryology Cerebellum Ultrasonography Echoencephalography Methods Imaging, Three-Dimensional Methods Ultrasonography, Prenatal Methods Algorithms Female Human Models, Statistical Pregnancy Reproducibility of Results Female ab: Previous work has shown that the segmentation of anatomical structures on 3D ultrasound data sets provides an important tool for the assessment of the fetal health. In this work, we present an algorithm based on a 3D statistical shape model to segment the fetal cerebellum on 3D ultrasound volumes. This model is adjusted using an ad hoc objective function which is in turn optimized using the Nelder-Mead simplex algorithm. Our algorithm was tested on ultrasound volumes of the fetal brain taken from 20 pregnant women, between 18 and 24 gestational weeks. An intraclass correlation coefficient of 0.8528 and a mean Dice coefficient of 0.8 between cerebellar volumes measured using manual techniques and the volumes calculated using our algorithm were obtained. As far as we know, this is the first effort to automatically segment fetal intracranial structures on 3D ultrasound data. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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