Medical Image Segmentation Using the Kohonen Neural Network


  • Carlos Alberto Tenório Carvalho UNIR


Image segmentation, Self-organizing maps of Kohonen, Edge detection, Medical imaging


An important definition of image segmentation is to divide an image into its features. This is a very important area in image processing field. The nontrivial image segmentation task is one of the most difficult challenges, since and there isn’t a unique suitable method to target all kinds of images so far. There are several researches related to image segmentation, some of them is the application of Self-Organizing Maps - SOM. In order to explore this method, that differs of the most used, such as the spatial filtering using derivative filters as detectors of edge Sobel, Prewitt, Roberts and Canny, thresholding techniques and Otsu method, this work aimed the medical image segmentation using the Kohonen neural network so itself adopts a non-supervised learning in the training process.


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How to Cite

Carvalho, C. A. T. (2019). Medical Image Segmentation Using the Kohonen Neural Network. IEEE Latin America Transactions, 17(2), 297–304. Retrieved from