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Reconstruction of 3D Cardiac MR Images from 2D Slices Using Directional Total Variation

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10555))

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.

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Acknowledgments

NMB acknowledges the support of the RCUK Digital Economy Programme grant number EP/G036861/1 (Oxford Centre for Doctoral Training in Healthcare Innovation). This work was supported by the British Heart Foundation (BHF) [grant numbers PG/13/33/30210, RG/13/8/30266, FS/11/50/29038 and NH/13/30238], the Engineering and Physical Sciences Research Council [grant number EP/J013250/1], and the BHF Centre for Research Excellence [grant number RE/13/1/30181. The authors acknowledge a Wellcome Trust Core Award [grant number 090532/Z/09/Z].

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Correspondence to Nicolas Basty .

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Basty, N., McClymont, D., Teh, I., Schneider, J.E., Grau, V. (2017). Reconstruction of 3D Cardiac MR Images from 2D Slices Using Directional Total Variation. In: Cardoso, M., et al. Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment. RAMBO CMMI SWITCH 2017 2017 2017. Lecture Notes in Computer Science(), vol 10555. Springer, Cham. https://doi.org/10.1007/978-3-319-67564-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-67564-0_13

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