MLP Neural Network Classifier for Medical Image Segmentation

The choice of a segmentation method depends on several considerations, namely the nature of the image, the primitives to extract and the segmentation methods. We propose an MLP-basis neuronal approach for the choice of the segmentation method taking into account the nature of the input image. First, an evaluation of the quality of segmentation by different methods and using various criteria of evaluation was carried out. Then, a characterization of images, based on some objective parameters, was performed. The resulting descriptors will be used as input to the neuronal approach to associate each type of image with the adequate segmentation method after learning. We report the results of the intelligent segmentation method choice obtained on different databases of medical images. The discussion of these encouraging results allowed us to improve our success rate and cover all varieties of images.