The Identification and Clustering Analysis of Auditory Neurons for Salicylated-Induced Rat Model

Author

Cheng, Kuo-Sheng ; Chen, Li-Hui ; Wang, Yi-Jung

Author_Institution

Inst. of Biomed. Eng., Nat. Cheng Kung Univ., Tainan

fYear

2006

Firstpage

6281

Lastpage

6284

Abstract

Salicylate-induced rat model is one of the animal models for tinnitus study. In this study, a radial basis function neural network for automatic identification is firstly developed due to its features of easy training and learning. From the experimental results, the recognition rate is demonstrated to be as high as 98%. Not only the recognition rate is improved, but also it is very objective in analysis. Secondly, a support vector clustering is applied to neurons distribution analysis. Based on the clustering analysis, it is found that the cluster number and distribution area for the Salicylated-induced fos-labeled neurons are very different from those of controlled group

Keywords

biomedical optical imaging; image recognition; medical image processing; molecular biophysics; neurophysiology; proteins; radial basis function networks; statistical analysis; support vector machines; Salicylated-induced fos-labeled neurons; Salicylated-induced rat model; auditory neurons; clustering analysis; neurons distribution analysis; radial basis function neural network; recognition rate; support vector clustering; tinnitus; Animals; Auditory system; Biomedical engineering; Image analysis; Image color analysis; Image processing; Neurons; Pattern analysis; Pattern recognition; Radial basis function networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

Conference_Location

Shanghai

Print_ISBN

0-7803-8741-4

Type

conf

DOI

10.1109/IEMBS.2005.1615933

Filename

1615933