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HAMMER: hierarchical attribute matching mechanism for elastic registration (2002)
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| Venue: | IEEE Trans. on Medical Imaging |
| Citations: | 278 - 95 self |
BibTeX
@ARTICLE{Shen02hammer:hierarchical,
author = {Dinggang Shen and Christos Davatzikos},
title = {HAMMER: hierarchical attribute matching mechanism for elastic registration},
journal = {IEEE Trans. on Medical Imaging},
year = {2002},
pages = {1421--1439}
}
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Abstract
A new approach is presented for elastic registration of medical images, and is applied to magnetic resonance images of the brain. Experimental results demonstrate remarkably high accuracy in superposition of images from different subjects, thus enabling very precise localization of morphological characteristics in population studies. There are two major novelties in the proposed algorithm. First, it uses an attribute vector, i.e. a set of geometric moment invariants that is defined on each voxel in an image, to reflect the underlying anatomy at different scales. The attribute vector, if rich enough, can distinguish between different parts of an image, which helps establish anatomical correspondences in the deformation procedure. This is a fundamental deviation of our method from other volumetric deformation methods, which are typically based on maximizing image similarity. Second, it employs a hierarchical deformation mechanism, which is initially influenced by parts of the anatomy that can be identified relatively more reliably than others. Moreover, the deformation mechanism involves a sequence of local smooth transformations, which do not update positions of individual voxels, but rather are based on evaluating a similarity of attribute vectors over a larger subvolume of a volumetric image. This renders this algorithm very robust to suboptimal solutions. A number of experiments in this paper have demonstrated excellent performance. 1.
Keyphrases
elastic registration attribute vector hierarchical attribute medical image major novelty precise localization deformation procedure morphological characteristic image similarity new approach high accuracy suboptimal solution volumetric image local smooth transformation volumetric deformation method hierarchical deformation mechanism different scale geometric moment invariant deformation mechanism different part magnetic resonance image anatomical correspondence individual voxels different subject population study fundamental deviation experimental result underlying anatomy excellent performance
