Medical image segmentation using a contextual-constraint-based hopfield neural cube

摘要

neural-network-based image techniques such as the Hopfield neural networks have been proposed as an alternative approach for image segmentation and have demonstrated benefits over traditional algorithms. However, due to its architecture limitation, image segmentation using traditional Hopfield neural networks results in the same function as thresholding of image histograms. With this technique high-level contextual information cannot be incorporated into the segmentation procedure. As a results, although the traditional Hopfield neural network was capable of segmenting noiseless images, it lacks the capability of noise robustness.