Research on Edge Detection of Medical Image Based on Wavelet Transform and Fuzzy Algorithm

Medical imaging has become an important basis for doctors in clinical diagnosis and treatment, which contains rich information about the human body. In order to present the diseased part of the body to the doctor in a more clear and intuitive way, the image must be processed. Therefore, the effectiveness of this method in medical images was proved in both subjective and objective aspects. Experiment by wavelet transform and fuzzy algorithm of medical image edge detection, improved method is applied to medical images, this paper chooses the size of a 512 x 512 abdominal CT images, and the image gaussian noise variance of 0.01, according to the calculated after denoising image peak signal-to-noise ratio (PSNR) and root mean square error (RMSE) to carry out the experimental evaluation. The experimental data show that the PSNR value is the highest and THE RMS value is the lowest after the threshold function processing in this paper. The experimental improved method has achieved good denoising effect when applied to medical images.