DocumentCode :
2257509
Title :
Behaviour analysis of micro-organisms to observe invisible substance effects: Towards the more sensitive biological effect detectors
Author :
Orun, A.B. ; Kurugollu, F. ; Seker, H.
Author_Institution :
Dept. of Inf., De Montfort Univ., Leicester, UK
fYear :
2012
fDate :
5-7 Jan. 2012
Firstpage :
608
Lastpage :
611
Abstract :
This work aims to introduce a sequence of novel methods and techniques which may be exploited towards the development of very sensitive “biological effect detector” which helps unveil the invisible biological effects of a substance which normally may not be discovered by the conventional laboratory experiments in a short term. The work presented here is regarded as the accomplishment an early stage of very sensitive biological detector configuration and promises to develop an ultimate novel compact system. By the experiments the chain of invisible behavioural characteristics of micro-organisms are identified by Bayesian inference method.
Keywords :
belief networks; image sequences; inference mechanisms; medical image processing; microorganisms; Bayesian inference method; behaviour analysis; biological effect detectors; conventional laboratory experiments; image sequence; invisible substance effects; micro-organisms; sensitive biological detector configuration; ultimate novel compact system; Animals; Biomedical imaging; Educational institutions; Materials; Solvents;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-2176-2
Electronic_ISBN :
978-1-4577-2175-5
Type :
conf
DOI :
10.1109/BHI.2012.6211656
Filename :
6211656
Link To Document :
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