Method for removing truncation artifacts in magnetic resonance images based on missing data reconstruction

Abstract

A method for removing truncation artifacts in magnetic resonance images based on missing data reconstruction belongs to the technical field of image processing and comprises the following steps: detecting the magnetic resonance images with the truncation artifacts to obtain low frequency K data; carrying out Fourier inversion on the low frequency K data in the frequency encoding direction to obtain a truncated spectrum G (kx, y) of one-dimensional Fourier transform in the phase encoding direction; extracting singularities and singular value in the images of each row of data of G (kx, y) and reconstructing each row of data to obtain the high frequency partial K data; and carrying out Fourier inversion on the high frequency partial K data Fy(k) to obtain the row information fy(x) of the magnetic resonance images with the artifacts removed and storing and combining fy(x) based on rows to form the magnetic resonance images g(x, y) with the artifacts removed. The method overcomes the artifact problem existing during imaging by zero padding, ensures high signal to noise ratio of the images, effectively reduces the image errors, precisely displays the original magnetic resonance images, provides high quality reliable image information for medical nuclear magnetic resonance detection and is conductive to development and popularization of medical imaging detection technology.

Description

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AI Technical Summary

Benefits of technology

This patented technique helps remove any unwanted parts or distortions from Magnet Resonography (MRT) images by utilizing an algorithm called lost data restoration. By doing this it overcomes problems caused during traditional methods like nullification techniques used beforehand. It also improves accuracy when displaying MRIs due to its ability to reduce noise levels without losing important details about what they are looking at. Overall, these improvements improve quality and reliability of MRI scans while reducing their impact on patients' healthcare costs.

Problems solved by technology

This patents describes different techniques for improving the accuracy and efficiency of removing noise from magnesistence tomography (mage). These techniques involve modifying the original signals before or after projection onto a screen to reduce interference between them. Additionally, they aim at reducing these effects while maintaining their effectiveness over long periods of scan times.

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