Basty, N, McClymont, D, Teh, I et al. (2 more authors) (2017) Reconstruction of 3D cardiac MR images from 2D slices using directional total variation. In: Cardoso, MJ, Arbel, T, Gao, F, Kainz, B, van Walsum, T, Shi, K, Bhatia, KK, Peter, R, Vercauteren, T, Reyes, M, Dalca, A, Wiest, R, Niessen, W and Emmer, BJ, (eds.) Lecture Notes in Computer Science. CMMI 2017, SWITCH 2017, RAMBO 2017, 14 Sep 2017, Quebec, Canada. Springer , pp. 127-135. ISBN 9783319675633
Abstract
Cardiac MRI allows for the acquisition of high resolution images of the heart. Long acquisition times of MRI make it impractical to image the full heart in 3D at high resolution. As a result, multiple 2D images are commonly acquired with a slice thickness greater than the in-plane resolution. One way of achieving isotropic high-resolution images is to apply post-processing techniques such as super-resolution to produce high resolution images from low resolution input. We use short-axis stacks as well as orthogonal long-axis views in a super-resolution framework, constraining the reconstruction using the contrast independent directional total variation algorithm to produce a high resolution 3D reconstruction with isotropic resolution. The 3D reconstruction retains the contrast of the short-axis stack, but incorporates the edge information from both the short-axis and the long-axis stacks. Results show improved reconstructions, with a segmentation voxel misclassification rate of 3.51% as opposed to 4.27% using linear interpolation.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2017, Springer International Publishing. This is an author produced version of a paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-67564-0_13 |
Keywords: | 3D image reconstruction; Super-resolution; Cardiac MRI; Regularisation; Directional total variation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Jan 2018 16:52 |
Last Modified: | 19 Jan 2018 10:05 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-319-67564-0_13 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:125494 |