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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3A3ALCL
Repositorysid.inpe.br/sibgrapi/2011/07.08.18.21
Last Update2011:07.08.18.21.38 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2011/07.08.18.21.38
Metadata Last Update2022:06.14.00.07.10 (UTC) administrator
DOI10.1109/SIBGRAPI.2011.46
Citation KeyFreitasRittAppeLotu:2011:WaSeMi
TitleWatershed-based segmentation of the midsagittal section of the corpus callosum in diffusion MRI
FormatDVD, On-line.
Year2011
Access Date2024, Apr. 30
Number of Files1
Size518 KiB
2. Context
Author1 Freitas, Pedro Ferro
2 Rittner, Leticia
3 Appenzeller, Simone
4 Lotufo, Roberto de Alencar
Affiliation1 School of Electrical and Computer Engineering, University of Campinas - UNICAMP
2 School of Electrical and Computer Engineering, University of Campinas - UNICAMP
3 Department of Medicine, Rheumatology Unit, University of Campinas - UNICAMP
4 School of Electrical and Computer Engineering, University of Campinas - UNICAMP
EditorLewiner, Thomas
Torres, Ricardo
e-Mail Addresspedroferro86@gmail.com
Conference NameConference on Graphics, Patterns and Images, 24 (SIBGRAPI)
Conference LocationMaceió, AL, Brazil
Date28-31 Aug. 2011
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2011-07-23 15:36:12 :: pedroferro86@gmail.com -> administrator :: 2011
2022-06-14 00:07:10 :: administrator -> :: 2011
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordscorpus callosum
fractional anisotropy
diffusion tensor imaging
magnetic resonance image
segmentation
watershed transform
AbstractThe corpus callosum (CC) is one of the most important white matter structures of the brain, interconnecting the two cerebral hemispheres. The corpus callosum is related to several neurodegenerative diseases and, as segmentation is usually the first step for studies in this structure, it is important to have a robust method for CC segmentation. We propose here a new approach for fully automatic segmentation of the CC in the magnetic resonance diffusion tensor images. The method uses the watershed transform and is performed on the fractional anisotropy (FA) map weighted by the projection of the principal eigenvector in the left-right direction. It first computes the section of the CC in the midsagittal slice and uses it as a seed for the 3D volume segmentation. Experiments with real diffusion MRI data showed that the proposed method is able to quickly segment the CC without any user intervention, with great results when compared to manual segmentation. Since it is simple, fast and does not require parameter settings, the proposed method is well suited for clinical applications.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2011 > Watershed-based segmentation of...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Watershed-based segmentation of...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3A3ALCL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3A3ALCL
Languageen
Target Fileexample.pdf
User Grouppedroferro86@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SKNPE
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.15.00.56 4
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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