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Proceedings Paper

Semi-automatic matching of OCT and IVUS images for image fusion
Author(s): Olivier Pauly; Gozde Unal; Greg Slabaugh; Stephane Carlier; Tong Fang
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Paper Abstract

Medical imaging is essential in the diagnosis of atherosclerosis. In this paper, we propose the semi-automatic matching of two promising and complementary intravascular imaging techniques, Intravascular Ultrasound (IVUS) and Optical Coherence Tomography (OCT), with the ultimate goal of producing hybrid images with increased diagnostic value for assessing arterial health. If no ECG gating has been performed on the IVUS and OCT pullbacks, there is typically an anatomical shuffle (displacement in time and space) in the image sequences due to the catheter motion in the artery during the cardiac cycle, and thus, this is not possible to perform a 3D registration. Therefore, the goal of our work is to detect semi-automatically the corresponding images in both modalities as a preprocessing step for the fusion. Our method is based on the characterization of the lumen shape by a set of Gabor Jets features. We also introduce different correction terms based on the approximate position of the slice in the artery. Then we train different support vector machines based on these features to recognize these correspondences. Experimental results demonstrate the usefulness of our approach, which achieves up to 95% matching accuracy for our data.

Paper Details

Date Published: 26 March 2008
PDF: 11 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69142N (26 March 2008); doi: 10.1117/12.773805
Show Author Affiliations
Olivier Pauly, Siemens Corporate Research (United States)
Gozde Unal, Siemens Corporate Research (United States)
Greg Slabaugh, Siemens Corporate Research (United States)
Stephane Carlier, Cardiovascular Research Foundation (United States)
Tong Fang, Siemens Corporate Research (United States)

Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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