Title
A practical salient region feature based 3D multi-modality registration method for medical images
Abstract
We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.
Year
DOI
Venue
2006
10.1117/12.653071
Proceedings of SPIE
Keywords
Field
DocType
hybrid registration,saliency,region features,multi-modality
Computer vision,Change detection,Invariant (physics),Pattern recognition,Salience (neuroscience),Outlier,Robustness (computer science),Artificial intelligence,Feature based,Cluster analysis,Geography,Salient
Conference
Volume
ISSN
Citations 
6144
0277-786X
2
PageRank 
References 
Authors
0.38
14
7
Name
Order
Citations
PageRank
Dieter A Hahn1384.40
Gabriele Wolz221.06
Yiyong Sun341428.70
Joachim Hornegger41734190.62
Frank Sauer517315.07
Torsten Kuwert6276.41
chenyang xu720.38