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dc.date.accessioned 2004-11-30T16:08:37Z
dc.date.available 2004-11-30T03:00:00Z
dc.date.issued 2004-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/9497
dc.description.abstract Skeletal age assessment is one of the important applications of hand radiography in the area of pediatric radiology. Features analysis of the carpal bones can reveal the important information for skeletal age assessment. The present work in this paper faces the problem of the detection of carpal-bone features from its radio-image. A novel and effective segmentation technique is presented in this work with carpal bone image for skeletal age estimation. Carpal bone segmentation is a critical operation of the automatic skeletal age assessment system. This method consists of three procedures. First, the original carpal bone image is preprocessed via anisotropic diffusion. Then, the carpal bone image is segmented by GVF-Snake model. Third, experiments are carried out on images of carpal bone. The results are very promising. In particular the method is able to extract overlapping carpal bones. en
dc.format.extent 152-156 es
dc.language en es
dc.subject IMAGE PROCESSING AND COMPUTER VISION es
dc.subject Radiografía es
dc.title Carpal-bone feature extraction analysis in skeletal age assessment based on deformable model en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct04-5.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Pan, Lin es
sedici.creator.person Zhang, Feng es
sedici.creator.person Yang, Yong es
sedici.creator.person Zheng, Chong-Xun es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000000433 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 4, no. 3 es


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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)