Research On Magnetic Resonance Image Processing Algorithms

Magnetic resonance imaging technique is applied widely because this technology has lots of features such as multi-imaging parameters, high resolution, non-invasive and arbitrary slice imaging, etc. However, this technology also has some defects such as required a long time during imaging, the images of soft tissue are low contrast, and lots of images have noise or artifacts. The spread and development of the magnetic resonance imaging technique are obstructed by these defects. In order to conquer those defects, this paper provides related processing algorithms on image enhancement and artifact correction.Firstly, in enhancement aspect, this paper improved a threshold processing algorithm based on scale dependencies to enhance the image. Consider in the same image, this paper considering that these two operations of image noise inhibition and enhance will affect each other, and lead to the image quality decline. Based on the characters of magnetic resonance image, according to the similarity between pixels this paper adopts a method that deal with the pixels differently, improve the enhancement algorithm on the basis of wavelet multi-scale product, using a threshold processing method based on the scale correlation to enhance the magnetic resonance image. The experiments show that this method can enhance the image effectively, and can inhibit and even eliminate the noise of the image at the same time.And then, two motion artifacts including translational motion artifact and rotational motion artifact are studied respectively. In the aspect of translational motion artifact, this paper adopts a method based on energy constraint to correct the artifact. On the basis of character analysis of the magnetic resonance image, this paper raised a algorithm based on energy constraint. This algorithm chooses direction information measure and the number of 0 pixels in the target zone of the magnetic resonance image as the energy function. Compare to the automatic reverse iterative algorithm, experiments show that this algorithm has certain advantages on correction of translational motion artifact. In the aspect of rotational motion artifact correction, this paper using a method based on sparse sampling to correct the rotating motion artifact of fast sequential magnetic resonance. Considering that after the correction of the K-space data, the data distribution will be uneven. Interpolation methods are often used to fill the data space, but the effect of the reconstruct image will change with different methods. Therefore, this paper selects sparse sampling imaging methods. K-space data has sparseness after transformation, in order to achieve sparse data space, we can use wavelet transform to transform the K-space data, then use the sparse sampling imaging. Experiments have proved that this method can correct the rotating motion artifact of magnetic resonance imaging effectively, and the effect of image reconstruction is good.