A multiscale/sparse representation for diffusion weighted imaging (DWI) super-resolution

Jonathan Tarquino; Andrea Rueda; Eduardo Romero

doi:10.1109/isbi.2014.6868037

A multiscale/sparse representation for diffusion weighted imaging (DWI) super-resolution

Jonathan Tarquino, Andrea Rueda, Eduardo Romero

Department of Systems Engineering

Universidad Nacional de Colombia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Spatial resolution of Diffusion Weighted (DW) images is currently limited by diverse considerations. This situation introduces a series of artifacts, such as the partial volume effect (PVE), that therefore affect the sensitivity of DW imaging analysis. In this paper, a new multiscale/sparse super-resolution method increases the spatial resolution of the DW images. Based on the redundancy presented in this kind of images, the proposed method uses local information and the multiscale shearlet transformation to closely approach the DW image acquisition process. A comparison of this proposal with a classical image interpolation method demonstrates an improvement of 2.27 dB in the PSNR measure and 1.67% in the SSIM metric.

Original language	English
Title of host publication	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	983-986
Number of pages	4
ISBN (Electronic)	9781467319591
DOIs	https://doi.org/10.1109/isbi.2014.6868037
State	Published - 29 Jul 2014
Event	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China Duration: 29 Apr 2014 → 02 May 2014

Publication series

Name	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Conference

Conference	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Country/Territory	China
City	Beijing
Period	29/04/14 → 02/05/14

Keywords

Information redundancy
Shearlet transform
Sparse representation
Super-resolution
Tensor representation

Access to Document

10.1109/isbi.2014.6868037

Cite this

Tarquino, J., Rueda, A., & Romero, E. (2014). A multiscale/sparse representation for diffusion weighted imaging (DWI) super-resolution. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 983-986). Article 6868037 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/isbi.2014.6868037

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abstract = "Spatial resolution of Diffusion Weighted (DW) images is currently limited by diverse considerations. This situation introduces a series of artifacts, such as the partial volume effect (PVE), that therefore affect the sensitivity of DW imaging analysis. In this paper, a new multiscale/sparse super-resolution method increases the spatial resolution of the DW images. Based on the redundancy presented in this kind of images, the proposed method uses local information and the multiscale shearlet transformation to closely approach the DW image acquisition process. A comparison of this proposal with a classical image interpolation method demonstrates an improvement of 2.27 dB in the PSNR measure and 1.67% in the SSIM metric.",

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Tarquino, J, Rueda, A & Romero, E 2014, A multiscale/sparse representation for diffusion weighted imaging (DWI) super-resolution. in 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014., 6868037, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Institute of Electrical and Electronics Engineers Inc., pp. 983-986, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Beijing, China, 29/04/14. https://doi.org/10.1109/isbi.2014.6868037

A multiscale/sparse representation for diffusion weighted imaging (DWI) super-resolution. / Tarquino, Jonathan; Rueda, Andrea; Romero, Eduardo.
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 983-986 6868037 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Spatial resolution of Diffusion Weighted (DW) images is currently limited by diverse considerations. This situation introduces a series of artifacts, such as the partial volume effect (PVE), that therefore affect the sensitivity of DW imaging analysis. In this paper, a new multiscale/sparse super-resolution method increases the spatial resolution of the DW images. Based on the redundancy presented in this kind of images, the proposed method uses local information and the multiscale shearlet transformation to closely approach the DW image acquisition process. A comparison of this proposal with a classical image interpolation method demonstrates an improvement of 2.27 dB in the PSNR measure and 1.67% in the SSIM metric.

AB - Spatial resolution of Diffusion Weighted (DW) images is currently limited by diverse considerations. This situation introduces a series of artifacts, such as the partial volume effect (PVE), that therefore affect the sensitivity of DW imaging analysis. In this paper, a new multiscale/sparse super-resolution method increases the spatial resolution of the DW images. Based on the redundancy presented in this kind of images, the proposed method uses local information and the multiscale shearlet transformation to closely approach the DW image acquisition process. A comparison of this proposal with a classical image interpolation method demonstrates an improvement of 2.27 dB in the PSNR measure and 1.67% in the SSIM metric.

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Tarquino J, Rueda A, Romero E. A multiscale/sparse representation for diffusion weighted imaging (DWI) super-resolution. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 983-986. 6868037. (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). doi: 10.1109/isbi.2014.6868037

A multiscale/sparse representation for diffusion weighted imaging (DWI) super-resolution

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