Research On Medical Image Enhancement And Segmentation Method Based On Wavelets

In recent years,with the practical application of wavelet analysis theory more and more widely,more and more full attention has been paid to it.Especially in the comprehensive processing of medical images,because the specific medical treatment level and human quality are different,and the diagnosis is affected by the external environment,medical images usually have certain noise pollution Medical image processing before medical diagnosis can repair the quality of images with low definition and low contrast,which can effectively reduce the possibility of misdiagnosis and greatly improve the accuracy of diagnosis.Because the human body tissue structure is particularly subtle and complex,the segmentation of medical image is also a particularly important part of contemporary medical image processing,and it can be widely used And it is one of the most complex parts.Up to now,there is no unified standard for medical image segmentation evaluation.This article mainly conducts in-depth research on Continuous wavelet transform,Dyadic wavelet transform and Biorthogonal wavelet transform.On this basis,it is proposed to combine wavelet transform with various frequency domain and spatial domain image processing methods to obtain better medical results.As an image enhancement method,a white matter segmentation method based on wavelet transform is proposed and it combines image enhancement and segmentation well.Through many experiments on the MATLAB experimental platform,the superiority and feasibility of the method proposed in this article are verified.The specific research content is as follows:(1)Using Haar wavelet,Db8 wavelet,Sym4 wavelet,Dior1.5 wavelet,Coif3 wavelet,and Dyadic wavelet principle respectively,an image enhancement model based on wavelet transform is established.Because medical images are complex,this article selects the effect The best nonlinear enhancement function is applied to medical image enhancement(preprocessing).The results of many experiments have proved that the medical image enhancement effect using dyadic wavelet is better.(2)A dyadic wavelet transform image segmentation model is established,and the first experiment uses the medical image enhancement method proposed in 4.1.2 of this paper to perform enhancement processing,and obtains whether it is objectively or subjectively.The enhanced image that is dominant in evaluation,and then image segmentation is performed on this image;the second experiment directly performs image segmentation on the original image;through the results of multiple experiments,it is obvious that the preprocessing proposed in this paper is used The effect of white matter segmentation is better and more accurate than the former.