Global Alignment of MR Images Using a Scale Based Hierarchical Model
Abstract
This paper proposes a novel automated method for global alignment of three dimensional MR images. The matching algorithm employed is closely related to a common constraint based tree searching algorithm [1], but uses a novel multi-resolution encoding of the search space to improve the search time and permit searching of curved surfaces. The algorithm uses the shape index defined by Koenderink [2] which provides the very useful property of invariance to uniform scale. The surfaces of the objects are extracted from the MR images automatically using a 3D deformable model [3]. An intelligent mechanism is used for selecting unusual surface features that are common to both objects.
Cite
Text
Fletcher et al. "Global Alignment of MR Images Using a Scale Based Hierarchical Model." European Conference on Computer Vision, 1996. doi:10.1007/3-540-61123-1_147Markdown
[Fletcher et al. "Global Alignment of MR Images Using a Scale Based Hierarchical Model." European Conference on Computer Vision, 1996.](https://mlanthology.org/eccv/1996/fletcher1996eccv-global/) doi:10.1007/3-540-61123-1_147BibTeX
@inproceedings{fletcher1996eccv-global,
title = {{Global Alignment of MR Images Using a Scale Based Hierarchical Model}},
author = {Fletcher, S. and Bulpitt, Andrew J. and Hogg, David C.},
booktitle = {European Conference on Computer Vision},
year = {1996},
pages = {283-292},
doi = {10.1007/3-540-61123-1_147},
url = {https://mlanthology.org/eccv/1996/fletcher1996eccv-global/}
}