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

Volume

1

fYear

1995

fDate

20-25 Sep 1995

Firstpage

835

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference

Conference_Location

Montreal, Que.

Print_ISBN

0-7803-2475-7

Type

conf

DOI

10.1109/IEMBS.1995.575387

Filename

575387