title: Volumetric object reconstruction using the 3D-MRF model-based segmentation.
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.
authors.affiliation: Department of Computer Science and Engineering, Ewha Womans University, Seoul, Korea.
authors.forename: S M
authors.initials: SM
authors.lastname: Choi
authors.forename: J E
authors.initials: JE
authors.lastname: Lee
authors.forename: J
authors.initials: J
authors.lastname: Kim
authors.forename: M H
authors.initials: MH
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007719:Knee Joint / Q000033:anatomy & histology; D008279:Magnetic Resonance Imaging