Maximizing structural similarity in multimodal biomedical microscopic images for effective registration

Title: Maximizing structural similarity in multimodal biomedical microscopic images for effective registration
Creator: Lv, Guohua; Teng, Shyh; Lu, Guojun; Lackmann, Martin
Date: 2013
Type: Text; Conference paper
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/161458
Identifier: vital:12480
Identifier: https://doi.org/10.1109/ICME.2013.6607629
Abstract: Multimodal image registration (MMIR) is the alignment of contents in images captured from different sensors or instruments. MMIR is important in medical applications as it enables the visualization of the complementary contents in biomedical microscopic images. The registration for such images can be challenging as the structures of their contents are usually only partially similar. Thus in this paper, we propose a new method to maximize the structural similarity of the contents in such images by utilizing intensity relationships among Red-Green-Blue color channels. Our experimental results will demonstrate that our proposed method substantially improves the accuracy of registering such images as compared to the state-of-the-art methods.
Publisher: IEEE
Relation: 2013 IEEE International Conference on Multimedia and Expo (ICME)
Rights: This metadata is freely available under a CCO license
Subject: 0801 Artificial Intelligence and Image Processing; Structural similarity; Staining; Intensity relationship; Multimodal image registration; SIFT
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