Method for image segmentation based on an encoder-segmented neural network and its application

Ning Li; Youfu Li

doi:10.1117/1.602050

1 May 1999 Method for image segmentation based on an encoder-segmented neural network and its application

Ning Li, Youfu Li

Optical Engineering, Vol. 38, Issue 5, (May 1999). https://doi.org/10.1117/1.602050

An Encoder-Segmented Neural Network (ESNN)-based approach is proposed to improve the efficiency of image segmentation. The features are ranked according to the encoder indicators by which the insignificant features will be eliminated from the original feature vectors and the important features reorganized as the encoded feature vectors for the subsequent clustering. The ESNN developed can improve on the existing Fuzzy c-Means (FCM) algorithm in feature extraction. The cluster number selection can be accomplished automatically. This method was successfully implemented for automatic labeling of tissues in MR brain images. Experimental results show that the ESNN-based approach offers satisfactory performance in both efficiency and adaptability.

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Ning Li and Youfu Li "Method for image segmentation based on an encoder-segmented neural network and its application," Optical Engineering 38(5), (1 May 1999). https://doi.org/10.1117/1.602050

Published: 1 May 1999

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