Nuclear magnetic image super-resolution system and method

Abstract

The invention relates to a nuclear magnetic image super-resolution system and method. The system comprises an image super-resolution training unit, an image super-resolution unit and a random parameter generator. The method includes performing degradation, interpolation and feature image extraction on an original nuclear magnetic image to obtain a feature image set, performing partition and vectorization on images in the feature image set to obtain a feature matrix and a target matrix of an image super-resolution training set, calculating weight vector parameters of neural network output nodes through the ELM (Extrem Learning Machine) principle, and selecting the optimal parameters from the weight vector parameters of the neural network output nodes to complete the image super-resolution training. According to the nuclear magnetic image super-resolution system and method, the original nuclear magnetic image is subjected to the degradation, interpolation, feature image extraction, partition and vectorization to obtain the feature matrix of the original nuclear magnetic image, and the ELM principle and the optimal parameters are used for obtaining super-resolution images of the original nuclear magnetic image through the feature matrix of the original nuclear magnetic image.

Description

technical field [0001] The invention belongs to the technical field of post-processing of medical images, and in particular relates to a system and method for nuclear magnetic image super-resolution. Background technique [0002] At present, MRI images have become an important detection method for clinical diagnosis, and the quality of MRI directly affects doctors' diagnosis of diseases. However, restricted by the development of nuclear magnetic resonance hardware, the method of nuclear magnetic image super-resolution has received more and more attention. At present, there are many related researches on image super-resolution. According to the input method, it can be divided into two categories, one is based on single image Image super-resolution technology, another type is based on multiple image input technology. However, there is no practical and effective super-resolution technology for nuclear magnetic images in these two types of technologies. Therefore, how to obtai...

AI Technical Summary

Problems solved by technology

[0003] In the existing research on image super-resolution algorithms, the processed image data is often too ideal, and the interference by noise is very small, and it can be processed by using the traditional super-resolution method; however, for non-optical methods to form The MRI images are subject to large noise interference, and due to the differences in the collected individual data, the previous super-resolution methods cannot improve the resolution while maintaining a high signal-to-noise ratio

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