Title :
Image segmentation with the spatiotemporal neuron and adaptive threshold learning
Author :
Richardson, Warren A. ; Kim, Soowon ; Waldron, Manjula B.
Author_Institution :
Dept. of Biomed. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
It is shown that a network of SpatioTEmporal Neurons (STEN), in combination with Adaptive Threshold Learning (ATL), can be used to segment images. The network performs the segmentation by temporally binding regions in the image with similar characteristics. Further, with proper selection of parameters, it is possible to extract related features such as edges and corners of regions. The authors have applied this method to segmenting a portion of an MRI image
Keywords :
adaptive signal processing; biomedical NMR; image segmentation; medical image processing; neural nets; MRI; adaptive threshold learning; magnetic resonance imaging; medical diagnostic imaging; parameters selection; region corners; region edges; spatiotemporal neuron; temporally binding regions; Artificial neural networks; Biological system modeling; Biomedical signal processing; Delay effects; Electronic switching systems; Equations; Helium; Image segmentation; Neurons; Spatiotemporal phenomena;
Conference_Titel :
Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference
Conference_Location :
Montreal, Que.
Print_ISBN :
0-7803-2475-7
DOI :
10.1109/IEMBS.1995.575387
