Volumetric object reconstruction using the 3D-MRF model-based segmentation [magnetic resonance imaging]

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. Here, the authors 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 the most 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 terms of image quality than the other methods.