The Singularity Detection Of Medical Image By Wavelet Transform

Wavelet Transform Theory, a new field developed in recent 10 years, is a time-dimension method of signal analysis. It has the characteristics of multi-resolution and can be used to describe the local characteristic of signal in both domain and frequency domain. Because of the excellent capability in signal processing, today wavelet transform has been used widely in image processing, signal filter, time and frequency analysis, multi-scale analysis, and so on. In biomedicine area, wavelet transform has been used mainly in signal detection, character pick-up, image processing, signal compression.Medical image includes lots of pathological information. It is important to clinical diagnosis and treatment. The computer medical image processing has been a hotspot to researchers at home and abroad. Therefore, it is very significant to explore more accurate and higher-speed automatic computer medical image processing.The task of medical image processing includes the image pretreatment, such as decompose, de-noise, enhancement, compress, feature extraction, image registration and fusion and 3D reconstruction, so on. The main content of this dissertation is to search a new method of image pretreatment to establish the foundation for the next more complex processing, to supply a new scientific means for clinic diagnosis and therapy. Medical image processing is the part of digital image processing. So we can process the medical image by general methods. However, the medical images have the characteristics of themselves. The general methods can't gain the ideal result sometimes. Therefore, the dissertation introduces a new wavelet method to treat with CT image of mezzanine of aorta.On the basis of proper wavelets selected and wavelet theory, we decompose CT image of aortic dissection by multi-scale successfully. We de-noise the CT image by soft threshold method successfully. We enhance...