An Abstract Accepted for Presentation in ISMRM2017 25TH Annual Meeting & Exhibition


The main of challenge of Magnetic Resonance Imaging (MRI) is dealing with high levels of noise which may corrupt the image especially since the noise is almost correlated with the image details. In this regard, we propose a new MRI enhancement method to overcome this limitation. The proposed MRI enhancement method relies on square sub-images enhancement depending on the noise level in each position using spatial adaptation of the Semi-Classical Signal Analysis (SCSA) method, where an enhancement parameter h is subject to a Gaussian distribution.

Figure.1: The proposed Gaussian distribution of h values ​​

The results show significant improvement in noise removal and preserving small details in the image.

Figure.2. Noisy (a.1), and denoised image with fixed (b.1) and variable h (c.1), zoom on the region A (displayed on a.1),

in the noisy (a.2), and denoised image with fixed (b.2) and variable h (c.2).​

An abstract of this work will be presented in 25th The International Society for Magnetic Resonance in Medicine (ISMRM) with following details:​

  • Abderrazak chahid, T.M. Laleg-Kirati, Hacene Serrai and Rik Achten, and, "Adaptive Magnetic Resonance Image signal enhancement using squared eigenfunctions of the Schrödinger operator", Accepted in ISMRM 25th Annual Meeting, Hawai, 2017.