Research On Accurate Segmentation Of Gray And White Matter Based On Mathematical Morphology

Objective: With the progress of science and technology, medical imaging hasbecome one of the fastest growing areas in medical technology, all kinds ofmedical images becomes strong scientific evidence in medical diagnosis andtreatment, in order to make it better for clinical application, medical imageprocessing technology has become an important research topic. To find a simple,accurate and effective medical image processing technology has been paid moreattention. The contrast between gray and white matter of CT images is notobvious, by the mathematical morphology, obtain the gray and white matterimage and then analyze the image,further segment the image.Lay the foundationfor biomedical research,clinical diagnosis, pathological analysis and so on.Methods: Mathematical morphology is a mathematical tool based on form toanalyze the morphological image, which has unique nonlinearcharacteristics.Mathematical morphology is applicable to all aspects of theimage processing. Give priority to mathematical morphology, based on itsbasic operation We can deduce and combine into various practical mathematicalmorphology algorithm.. In combination with the traditional linear algorithm,using the Labview software and IMAQ software to realize the segmentation ofbrain CT image.Results: Getting an accurate，simple and practical segmentation proceduresbased on mathematical morphology and its various practical mathematicalmorphology algorithm, First of all, to extract the internal structure of thebrain，and then to segment well gray and white matter of brain image, and toshow respectively the gray and white matter, thus to provide a certain guiding significance to brain disease.Conclusion: The method of mathematical morphology can be well applied to themedical image processing, can become the new focus on medical image processingtechnology, and can bring a new opportunity for medical image processing; TheLabview software not only can beused in signal processing, also be suitable for image processing, and add anew platform for image processing.