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Quantitative Evaluation of Correction Methods and Simulation of Motion Artifacts for Rotary Pullback Imaging Catheters

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Medical Image Understanding and Analysis (MIUA 2018)

Abstract

In this work, we present a quantitative study based on the ground truth image and artificial motion artifacts and its correction using azimuthal en face image registration (AEIR) method. Motion artifacts in the in vivo imaging make identification of features and structures like blood vessels challenging. Correction of distortions of tissue features resultant from motion artifacts may enhance image quality and interpretation of images. Optical coherence tomography (OCT) and autofluorescence imaging (AFI) has been reported for in vivo endoscopic imaging. Motion artifacts in pulmonary OCT-AFI data sets may be estimated from both AFI and OCT images based on azimuthal registration of slowly varying structures in the 2D en face image. In our previous work, we have described a simulation of motion artifacts for 3D or 2D rotational catheter data and AEIR method, correcting motion artifacts. Our simulated artifacts may be applied on a ground truth image to create an image with known artifacts for the quantitative evaluation of performance of the correction methods. Since there might be some non-visible motion artifacts in the original ground truth image, we need apply the correction method before applying the simulated artifacts. However, there is no guarantee that this process converges to a motion-free scan; also the pre-corrected ground truth image is subjected to the correction method for further quantitative analysis. Here, we present a study for quantitative evaluations on a ground truth image of in silico phantom, NURD phantom and in vivo OCT and AF images.

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Acknowledgment

This work was supported by Canadian institutes of health research (CIHR) (ppp-141717).

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Correspondence to Elham Abouei .

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Abouei, E., Lee, A.M.D., Hohert, G., Lane, P., Lam, S., MacAulay, C. (2018). Quantitative Evaluation of Correction Methods and Simulation of Motion Artifacts for Rotary Pullback Imaging Catheters. In: Nixon, M., Mahmoodi, S., Zwiggelaar, R. (eds) Medical Image Understanding and Analysis. MIUA 2018. Communications in Computer and Information Science, vol 894. Springer, Cham. https://doi.org/10.1007/978-3-319-95921-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-95921-4_8

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  • Online ISBN: 978-3-319-95921-4

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