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An atlas-based multimodal registration method for 2D images with discrepancy structures

An atlas-based multimodal registration method for 2D images with discrepancy structures An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Medical & Biological Engineering & Computing Springer Journals

An atlas-based multimodal registration method for 2D images with discrepancy structures

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Publisher
Springer Journals
Copyright
Copyright © 2018 by International Federation for Medical and Biological Engineering
Subject
Biomedicine; Human Physiology; Biomedical Engineering; Imaging / Radiology; Computer Applications
ISSN
0140-0118
eISSN
1741-0444
DOI
10.1007/s11517-018-1808-1
Publisher site
See Article on Publisher Site

Abstract

An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures.

Journal

Medical & Biological Engineering & Computing – Springer Journals

Published: Jun 4, 2018

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