Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김명희 | * |
dc.date.accessioned | 2018-06-02T08:15:08Z | - |
dc.date.available | 2018-06-02T08:15:08Z | - |
dc.date.issued | 1997 | * |
dc.identifier.issn | 0278-0062 | * |
dc.identifier.other | OAK-17027 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/244410 | - |
dc.description.abstract | A number of segmentation algorithms have been developed, but those algorithms are not effective on volume reconstruction because they are limited to operating only on two-dimensional (2-D) images. In this paper, we propose the volumetric object reconstruction method using the three-dimensional Markov random field (3D-MRF) model-based segmentation. The 3D-MRF model is known to be one of efficient ways to model spatial contextual information. The method is compared with the 2-D region growing scheme under three types of interpolation. The results show that the proposed method is better in the aspect of image quality than other methods. © 1997 IEEE. | * |
dc.language | English | * |
dc.title | Volumetric object reconstruction using the 3D-MRF model-based segmentation | * |
dc.type | Article | * |
dc.relation.issue | 6 | * |
dc.relation.volume | 16 | * |
dc.relation.index | SCI | * |
dc.relation.index | SCIE | * |
dc.relation.index | SCOPUS | * |
dc.relation.startpage | 887 | * |
dc.relation.lastpage | 892 | * |
dc.relation.journaltitle | IEEE Transactions on Medical Imaging | * |
dc.identifier.scopusid | 2-s2.0-0031283419 | * |
dc.author.google | Choi S.M. | * |
dc.author.google | Lee J.E. | * |
dc.author.google | Kim J. | * |
dc.author.google | Kim M.H. | * |
dc.contributor.scopusid | 김명희(34770838100) | * |
dc.date.modifydate | 20240322133114 | * |