A practical salient region feature based 3D multi-modality registration method for medical images

Hahn D, Wolz G, Sun Y, Hornegger J, Sauer F, Kuwert T, Xu C (2006)

Publication Type: Conference contribution, Conference Contribution

Publication year: 2006

Journal

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Original Authors: Hahn D., Wolz G., Sun Y., Hornegger J., Sauer F., Kuwert T., Xu C.

Book Volume: null

Pages Range: -

Event location: San Diego, CA

Journal Issue: null

DOI: 10.1117/12.653071

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.

Authors with CRIS profile

Joachim Hornegger Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) Torsten Kuwert Lehrstuhl für Klinische Nuklearmedizin

Involved external institutions

Siemens Corporate Research US United States (USA) (US)

How to cite

APA:

Hahn, D., Wolz, G., Sun, Y., Hornegger, J., Sauer, F., Kuwert, T., & Xu, C. (2006). A practical salient region feature based 3D multi-modality registration method for medical images. In Proceedings of the Medical Imaging 2006: Image Processing (pp. -). San Diego, CA.

MLA:

Hahn, Dieter, et al. "A practical salient region feature based 3D multi-modality registration method for medical images." Proceedings of the Medical Imaging 2006: Image Processing, San Diego, CA 2006. -.

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