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An efficient medical image classification using deep learning techniques

Adaline Suij R

Objective: Image Processing will be preparing of pictures utilizing numerical activity by utilizing some other sign handling for which the info is a picture. The yield of picture handling might be either a picture or some other structure identified with picture. Method: In therapeutic application Image Fusion is the way toward consolidating pertinent data from at least two pictures into a sign picture. The subsequent melded picture will be more instructive than any of the yield pictures. The division and order are utilized to discover the tumor part in the melded picture. Different existing multi scale change, for example, DWT, ST, DTWT, DCT produces curios in the intertwined picture. Another restorative picture combination plot dependent on a Stationary Wavelet Transform is proposed. Result: The First procedure is to apply the preprocessing technique to expel the clamor from the picture. Stationary Wavelet change is utilized to deteriorate the picture. Morphological work is utilized to extricate the component of the picture. The proposed picture gives the top notch picture when contrasted with past technique. At last, division and grouping strategies are utilized to locate the influenced zone in the melded picture. Conclusion: For Segmentation GMM (Gaussian Mixture Model) is proposed. For arrangement CNN (Convolutional Neural Networks) is proposed. In this proposed technique CT and MRI pictures are utilized as info picture to deliver progressively useful picture.