Non-local MRI upsampling

Manjón, José V.; Coupé, Pierrick; Buades, Antonio; Fonov, Vladimir; Louis Collins, D.; Robles, Montserrat

doi:10.1016/j.media.2010.05.010

« PreviousMedical Image Analysis
Volume 14, Issue 6 , Pages 784-792, December 2010

Non-local MRI upsampling

José V. Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022 Valencia, Spain
- Corresponding author. Tel.: +34 96 387 70 00x75275; fax: +34 96 387 90 09.
Pierrick Coupé
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
Antonio Buades
- Université Paris Descartes, 45 rue des Saints Pères, 75270 Paris Cedex 06, France
- Dpt. Matemàtiques i Informàtica, Universitat Illes Balears, Ctra Valldemossa km 7.5, 07122 Palma de Mallorca, Spain
Vladimir Fonov
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
D. Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
Montserrat Robles
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022 Valencia, Spain

Received 16 September 2009; received in revised form 26 March 2010; accepted 31 May 2010. published online 07 June 2010.

Abstract

In Magnetic Resonance Imaging, image resolution is limited by several factors such as hardware or time constraints. In many cases, the acquired images have to be upsampled to match a specific resolution. In such cases, image interpolation techniques have been traditionally applied. However, traditional interpolation techniques are not able to recover high frequency information of the underlying high resolution data. In this paper, a new upsampling method is proposed to recover some of this high frequency information by using a data-adaptive patch-based reconstruction in combination with a subsampling coherence constraint. The proposed method has been evaluated on synthetic and real clinical cases and compared with traditional interpolation methods. The proposed method is shown to outperform classical interpolation methods compared in terms of quantitative measures and visual observation.

Keywords: MRI, Interpolation, Super resolution

Abbreviations: NLM, non-local means, MNLM3D, multiresolution non-local means 3D, SNR, signal to noise ratio, PSNR, peak signal to noise ratio, LR, low resolution, HR, high resolution, SR, super resolution, DTI, diffusion tensor imaging