MLP neural network classifier for medical image segmentation - 2016 PROJECT TITLE : MLP neural network classifier for medical image segmentation - 2016 ABSTRACT: The selection of a segmentation methodology depends on several concerns, particularly the character of the image, the primitives to extract and therefore the segmentation ways. We have a tendency to propose an MLP-basis neuronal approach for the selection of the segmentation methodology taking into consideration the character of the input image. First, an analysis of the standard of segmentation by completely different ways and using numerous criteria of evaluation was distributed. Then, a characterization of pictures, based on some objective parameters, was performed. The ensuing descriptors will be used as input to the neuronal approach to associate each type of image with the adequate segmentation methodology when learning. We report the results of the intelligent segmentation methodology choice obtained on totally different databases of medical images. The discussion of those encouraging results allowed us to boost our success rate and cowl all styles of images. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Image Segmentation Medical Image Processing Image Classification Multilayer Perceptrons Mlp-Basis Neuronal Locality sensitive deep learning for detection and Classification of nuclei in routine colon cancer Histology images - 2016 Nonparametric joint shape and feature priors for segmentation of Dendritic spines - 2016
