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Reference TypeConference Proceedings
Identifier6qtX3pFwXQZG2LgkFdY/MfvP7
Repositorysid.inpe.br/sibgrapi@80/2006/08.24.15.21
Metadatasid.inpe.br/sibgrapi@80/2006/08.24.15.21.56
Sitesibgrapi.sid.inpe.br
Citation KeyLeandroCésaCost:2006:DeBr3D
Author1 Leandro, Jorge de Jesus Gomes
2 César Júnior, Roberto Marcondes
3 Costa, Luciano da Fontoura
Affiliation1 Institute of Mathematics and Statistics - University of São Paulo - IME/USP
2 Institute of Mathematics and Statistics - University of São Paulo - IME/USP
3 Department of Physics and Informatics - Institute of Physics of São Carlos - USP
TitleDetermining the branchings of 3D structures from respective 2D projections
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 19 (SIBGRAPI)
Year2006
EditorOliveira Neto, Manuel Menezes de
Carceroni, Rodrigo Lima
Book TitleProceedings
Date8-11 Oct. 2006
Publisher CityLos Alamitos
PublisherIEEE Computer Society
Conference LocationManaus
Keywordsneurons, shape, branchings, crossings.
AbstractThis work describes a new framework for automatic extraction of 2D branching structures images obtained from 3D shapes, such as neurons and retinopathy images. The majority of methods for neuronal cell shape analysis that are based on the 2D contours of cells fall short of properly characterizing such cells because crossings among neuronal processes constrain the access of contour following algorithms to the innermost regions of the cell. The framework presented in this article addresses, possibly for the first time, the problem of determining the continuity along crossings, therefore granting to the contour following algorithm full access to all processes of the neuronal cell under analysis. First, the raw image is preprocessed so as to obtain an 8-connected, one-pixel wide skeleton as well as a set of seed pixels for each subtree and all the branching/crossing regions. Then, for each seed pixel, the algorithm labels all valid neighbors, until a branching/crossing region is reached, when a decision about the proper continuation is taken based on the tangent continuity. The algorithm has shown robustness for images with parallel segments and low densities of branching/crossing densities. The problem of too high densities of branching/crossing regions can be addressed by using a suitable data structure. Successful experimental results using real data (neural cell images) are presented.
Languageen
Tertiary TypeFull Paper
FormatOn-line
Size241 KiB
Number of Files1
Target Fileleandro-branching.pdf
Last Update2006:08.24.15.21.55 sid.inpe.br/banon/2001/03.30.15.38 administrator
Metadata Last Update2020:02.19.03.17.48 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2006}
Document Stagecompleted
Is the master or a copy?is the master
e-Mail Addressjleandro@vision.ime.usp.br
User Groupjleandro administrator
Visibilityshown
Transferable1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
Content TypeExternal Contribution
source Directory Contentthere are no files
agreement Directory Contentthere are no files
History2006-08-24 15:21:56 :: jleandro -> banon ::
2006-08-30 21:53:44 :: banon -> jleandro ::
2008-07-17 14:11:04 :: jleandro -> administrator ::
2009-08-13 20:38:15 :: administrator -> banon ::
2010-08-28 20:02:25 :: banon -> administrator ::
2020-02-19 03:17:48 :: administrator -> :: 2006
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group holdercode isbn issn label lineage mark mirrorrepository nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume
Access Date2020, Nov. 25

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