Abstract
Diffusion-weighted imaging (DWI) enables non-invasive investigation and characterization of the white-matter but suffers from a relatively poor resolution. In this work we propose a super-resolution reconstruction (SRR) technique based on the acquisition of multiple anisotropic orthogonal DWI scans. We address the problem of patient motions by aligning the volumes both in space and in q-space. The SRR is formulated as a maximum a posteriori (MAP) problem. It relies on a volume acquisition model which describes the generation of the acquired scans from the unknown high-resolution image. It enables the introduction of image priors that exploit spatial homogeneity and enables regularized solutions. We detail our resulting SRR optimization procedure and report various experiments including numerical simulations, synthetic SRR scenario and real world SRR scenario. Super-resolution reconstruction in DWI may enable DWI to be performed with unprecedented resolution.
Chapter PDF
Similar content being viewed by others
References
Calamante, F., Tournier, J.-D., Jackson, G.D., Connelly, A.: Track-density imaging (TDI): super-resolution white matter imaging using whole-brain track-density mapping. NeuroImage 53(4), 1233–1243 (2010)
Gholipour, A., Estroff, J.A., Warfield, S.K.: Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans. on Med. Imag. 29(10), 1739–1758 (2010)
Greenspan, H.: MRI inter-slice reconstruction using super-resolution. Magn. Res. Imag. 20(5), 437–446 (2002)
Greenspan, H.: Super-Resolution in Medical Imaging. Comput. J. 52(1), 43–63 (2009)
Holland, D., Kuperman, J.M., Dale, A.M.: Efficient correction of inhomogeneous static magnetic field-induced distortion in echo planar imaging. NeuroImage 50(1), 175–183 (2010)
Irani, M., Peleg, S.: Motion Analysis for Image Enhancement: Resolution, Occlusion, and Transparency. J. Vis. Com. and Image Rep. 4(4), 324–335 (1993)
Jiang, S., Xue, H., Counsell, S., Anjari, M., Allsop, J., Rutherford, M., Rueckert, D., Hajnal, J.V.: Diffusion tensor imaging (DTI) of the brain in moving subjects: application to in-utero fetal and ex-utero studies.. Magn. Res. in Med. 62(3), 645–655 (2009)
Matheron, G.: Principles of geostatistics. Economic Geology 58(8), 1246–1266 (1963)
Peled, S., Yeshurun, Y.: Superresolution in MRI: application to human white matter fiber tract visualization by diffusion tensor imaging.. Magn. Res. in Med. 45(1), 29–35 (2001)
Windischberger, C., Robinson, S., Rauscher, A., Barth, M., Moser, E.: Robust field map generation using a triple-echo acquisition. J. Magn. Reson. Imaging 20(4), 730–734 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Scherrer, B., Gholipour, A., Warfield, S.K. (2011). Super-Resolution in Diffusion-Weighted Imaging. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6892. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23629-7_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-23629-7_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23628-0
Online ISBN: 978-3-642-23629-7
eBook Packages: Computer ScienceComputer Science (R0)