Magnetic resonance super undersampled K data imaging method based on studying generalized double-layer Bergman non-convex-type dictionary

Abstract

The invention discloses a magnetic resonance super undersampled K data imaging method based on studying a generalized double-layer Bergman non-convex-type dictionary. The imaging method includes the steps that 1 prior information with non-convex function p norm is blended into a double-layer Bergman dictionary study frame, the dictionary study and coefficient sparsity are conducted, and an image sparse representation model is established; 2 by using an increasing auxiliary variable and alternating technology, the dictionary study and coefficient sparsity are updated in an inner-layer iteration of the double-layer Bergman iterative dictionary study, an objective function of the prior information with the non-convex p norm is obtained by using a generalized soft threshold iterative method particularly, and the sparse coefficients are updated; 3 the image is updated in an outer-layer iteration of the double-layer Bergman dictionary study, and a reconstructed image is obtained. By means of the generalized soft threshold iterative method, the objective function of the prior information with non-convex p norm is obtained, small coefficients can be punished in a larger range and large coefficients are smaller in deviation, a sparse representation image can be further obtained, the image can be accurately reconstructed with less scan measurement, artifacts of the reconstructed image are reduced, and more image details are recovered.

Description

technical field [0001] The invention belongs to the field of medical imaging, in particular to magnetic resonance imaging. Background technique [0002] Magnetic resonance imaging is an examination technology that uses images for medical diagnosis. It has no ionizing radiation damage and can directly scan images of various layers of the human body. Therefore, magnetic resonance imaging can provide doctors with clear and practical images of the internal structure of the human body. [0003] However, the main disadvantage of the magnetic resonance imaging system is that the imaging speed is slow, which greatly reduces the indications of magnetic resonance imaging examinations, such as not suitable for the examination of moving organs and the examination of critically ill patients, and for noise or loss of self-control Certain applications in pediatrics are also limited in patients who are difficult to image without sedation. Therefore, since the advent of magnetic resonance ...

AI Technical Summary

Problems solved by technology

The double-layer Bergman dictionary learning algorithm proposed by Liu Qigen et al. uses the l1 norm to approximate the l0 norm to obtain an equivalent solution, but after the transformation The small coefficient is approximately zero and the deviation of the large coefficient is large, which will make the anatomical structure of the reconstructed image unclear and appear aliasing

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