Review On: An Efficient Technique of Noising and De-Noising Medical Images Using Neuro– FUZZY and LDA

Medical imaging technology is becoming an important component of large number of applications such as diagnosis, research, and treatment. Medical images like X-Ray, CT, MRI, PET and SPECT have minute information about heart brain and nerves. These images need to be accurate and free from noise. Noise reduction plays an important role in medical imaging. Various method of noise removal such as filters, wavelets and thresholding based on wavelets. Although these methods produced good results but still have some limitations. Considering and analyzing the limitations of the previous methods our research presents neural networks as an efficient and robust tool for noise reduction [1,7]. In our research we use Neuro –Fuzzy and LDA as the learning algorithm which follows the supervised learning. The proposed research use both mean and median statistical functions for calculating the output pixels results in terms of PSNR and MSE.