Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images
We present a robust method for automatically constructing an ellipsoidal skeleton (e-skeleton) from a set of 3D points taken from NMR or TDM images. To ensure steadiness and accuracy, all points of the objects are taken into account, including the inner ones, which is different from the existing techniques. This skeleton will be essentially useful for object characterization, for comparisons between various measurements and as a basis for deformable models. It also provides good initial guess for surface reconstruction algorithms. On output of the entire process, we obtain an analytical description of the chosen entity, semantically zoomable (local features only or reconstructed surfaces), with any level of detail (LOD) by discretization step control in voxel or polygon format. This capability allows us to handle objects at interactive frame rates once the e-skeleton is computed. Each e-skeleton is stored as a multiscale CSG implicit tree.
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Subjects: | U10 - Informatique, mathématiques et statistiques, imagerie, sciences médicales, modèle mathématique, radiographie, partie du corps, http://aims.fao.org/aos/agrovoc/c_36760, http://aims.fao.org/aos/agrovoc/c_4695, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_6428, http://aims.fao.org/aos/agrovoc/c_981, |
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dig-cirad-fr-4012902024-01-28T01:15:57Z http://agritrop.cirad.fr/401290/ http://agritrop.cirad.fr/401290/ Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images. Banegas Frédéric, Michelucci Dominique, Roelens Marc, Jaeger Marc. 1999. In : Medical imaging 1999. Image processing = [Imagerie médicale 1999. Traitement d'image]. Hanson K.M. (ed.). s.l. : SPIE, 1227-1237. SPIE Conference on Image Processing, San Diego, États-Unis, 22 Février 1999/25 Février 1999. Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images Banegas, Frédéric Michelucci, Dominique Roelens, Marc Jaeger, Marc eng 1999 SPIE Medical imaging 1999. Image processing = [Imagerie médicale 1999. Traitement d'image] U10 - Informatique, mathématiques et statistiques imagerie sciences médicales modèle mathématique radiographie partie du corps http://aims.fao.org/aos/agrovoc/c_36760 http://aims.fao.org/aos/agrovoc/c_4695 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6428 http://aims.fao.org/aos/agrovoc/c_981 We present a robust method for automatically constructing an ellipsoidal skeleton (e-skeleton) from a set of 3D points taken from NMR or TDM images. To ensure steadiness and accuracy, all points of the objects are taken into account, including the inner ones, which is different from the existing techniques. This skeleton will be essentially useful for object characterization, for comparisons between various measurements and as a basis for deformable models. It also provides good initial guess for surface reconstruction algorithms. On output of the entire process, we obtain an analytical description of the chosen entity, semantically zoomable (local features only or reconstructed surfaces), with any level of detail (LOD) by discretization step control in voxel or polygon format. This capability allows us to handle objects at interactive frame rates once the e-skeleton is computed. Each e-skeleton is stored as a multiscale CSG implicit tree. conference_item info:eu-repo/semantics/conferenceObject Conference info:eu-repo/semantics/closedAccess http://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=98209 |
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U10 - Informatique, mathématiques et statistiques imagerie sciences médicales modèle mathématique radiographie partie du corps http://aims.fao.org/aos/agrovoc/c_36760 http://aims.fao.org/aos/agrovoc/c_4695 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6428 http://aims.fao.org/aos/agrovoc/c_981 U10 - Informatique, mathématiques et statistiques imagerie sciences médicales modèle mathématique radiographie partie du corps http://aims.fao.org/aos/agrovoc/c_36760 http://aims.fao.org/aos/agrovoc/c_4695 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6428 http://aims.fao.org/aos/agrovoc/c_981 |
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U10 - Informatique, mathématiques et statistiques imagerie sciences médicales modèle mathématique radiographie partie du corps http://aims.fao.org/aos/agrovoc/c_36760 http://aims.fao.org/aos/agrovoc/c_4695 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6428 http://aims.fao.org/aos/agrovoc/c_981 U10 - Informatique, mathématiques et statistiques imagerie sciences médicales modèle mathématique radiographie partie du corps http://aims.fao.org/aos/agrovoc/c_36760 http://aims.fao.org/aos/agrovoc/c_4695 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6428 http://aims.fao.org/aos/agrovoc/c_981 Banegas, Frédéric Michelucci, Dominique Roelens, Marc Jaeger, Marc Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images |
description |
We present a robust method for automatically constructing an ellipsoidal skeleton (e-skeleton) from a set of 3D points taken from NMR or TDM images. To ensure steadiness and accuracy, all points of the objects are taken into account, including the inner ones, which is different from the existing techniques. This skeleton will be essentially useful for object characterization, for comparisons between various measurements and as a basis for deformable models. It also provides good initial guess for surface reconstruction algorithms. On output of the entire process, we obtain an analytical description of the chosen entity, semantically zoomable (local features only or reconstructed surfaces), with any level of detail (LOD) by discretization step control in voxel or polygon format. This capability allows us to handle objects at interactive frame rates once the e-skeleton is computed. Each e-skeleton is stored as a multiscale CSG implicit tree. |
format |
conference_item |
topic_facet |
U10 - Informatique, mathématiques et statistiques imagerie sciences médicales modèle mathématique radiographie partie du corps http://aims.fao.org/aos/agrovoc/c_36760 http://aims.fao.org/aos/agrovoc/c_4695 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6428 http://aims.fao.org/aos/agrovoc/c_981 |
author |
Banegas, Frédéric Michelucci, Dominique Roelens, Marc Jaeger, Marc |
author_facet |
Banegas, Frédéric Michelucci, Dominique Roelens, Marc Jaeger, Marc |
author_sort |
Banegas, Frédéric |
title |
Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images |
title_short |
Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images |
title_full |
Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images |
title_fullStr |
Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images |
title_full_unstemmed |
Hierarchical automated clustering of cloud point set by ellipsoidal skeleton. Application to organ geometric modeling from CT-scan images |
title_sort |
hierarchical automated clustering of cloud point set by ellipsoidal skeleton. application to organ geometric modeling from ct-scan images |
publisher |
SPIE |
url |
http://agritrop.cirad.fr/401290/ |
work_keys_str_mv |
AT banegasfrederic hierarchicalautomatedclusteringofcloudpointsetbyellipsoidalskeletonapplicationtoorgangeometricmodelingfromctscanimages AT micheluccidominique hierarchicalautomatedclusteringofcloudpointsetbyellipsoidalskeletonapplicationtoorgangeometricmodelingfromctscanimages AT roelensmarc hierarchicalautomatedclusteringofcloudpointsetbyellipsoidalskeletonapplicationtoorgangeometricmodelingfromctscanimages AT jaegermarc hierarchicalautomatedclusteringofcloudpointsetbyellipsoidalskeletonapplicationtoorgangeometricmodelingfromctscanimages |
_version_ |
1792492065630715904 |