The Research On Techniques For Image Denoising And Edge Detection In CT Image Of The Brain Department Baded On EMD And Wavelet

Medical imageology has become one of fields on medical technology that develop most quickly for nearly more than 20 years.It has been applied extensively in diagnosis and treatment,and maken the observation for the internal position of human body of pathological changes more direct, more distinct.So,the diagnose rate is higher. It has also become essential means and tool.Analysis and processing in medical image are a very important part in medical imageology technology.Especially image denoisinging and edge detection in areas of image processing are also become a hotspot in researching.But because the medical image processing level is lower, what's more, the utilization rate for signal is still not enough.we realizes the diagnosis for relevant disease is basically depent on doctors whose richen clinical experience and use the observation with naked eyes for the medical image after Inspecting to definite diagnosis. Using some imagine processing technology, we can process the medical image efficiently and in a deeper level.For example, image denoisinging, strengthening and mixing together as well as edge detection etc., so as to improving the utilization rate for medical image information. It is helpful for drawing information of pathological changes features, and improving accuracy rate of diagnosis.This paper has introduced the development of medical imagie processing technology, the scope and methods.Then it made denoising and edge detection for the CT image of the brain aiming at the properties and keystoned of CT image.In the process of denosing for CT images of the brain,because it has some characteristics,such as the biomedical signal is a typical non-stationary signal with a strong noise in background,it is more difficult to resolution.So the paper introuduced a method of denoising CT image of the brain based on EMD,which can effectively remove noise,then the local features of the signals fully retained.CT image of the vague imformation and the edge detection showed weak performances,we use fast fuzzy wavelet algorithms for edge detection.The edge detection algorithms based on wavelet and fast fuzzy, has the characteristics of multi-resolution analysis and separate from the low-frequency and high-frequency edges.Fast and fuzzy edge detection algorithm improves the classic Pal and King's edge detection algorithmn and use the simple membership function.It can comple the conversion of image attached to the membership matrix inverse inverse matrix of image change fast.Thewavelet decomposition of the low-frequency signal which contains useful imformation to be used simplified algorithm and improved the efficiency, and enhanced the adaptability of the metho.Finally, the experimental results show that the denoising results clearly when the proposed algorithm compared with other methods,it also be more precise and can be detected in a clear edge images.