Document Detail

Vision-based force measurement using neural networks for biological cell microinjection.
MedLine Citation:
PMID:  24411067     Owner:  NLM     Status:  Publisher    
This paper presents a vision-based force measurement method using an artificial neural network model. The proposed model is used for measuring the applied load to a spherical biological cell during micromanipulation process. The devised vision-based method is most useful when force measurement capability is required, but it is very challenging or even infeasible to use a force sensor. Artificial neural networks in conjunction with image processing techniques have been used to estimate the applied load to a cell. A bio-micromanipulation system capable of force measurement has also been established in order to collect the training data required for the proposed neural network model. The geometric characterization of zebrafish embryos membranes has been performed during the penetration of the micropipette prior to piercing. The geometric features are extracted from images using image processing techniques. These features have been used to describe the shape and quantify the deformation of the cell at different indentation depths. The neural network is trained by taking the visual data as the input and the measured corresponding force as the output. Once the neural network is trained with sufficient number of data, it can be used as a precise sensor in bio-micromanipulation setups. However, the proposed neural network model is applicable for indentation of any other spherical elastic object. The results demonstrate the capability of the proposed method. The outcomes of this study could be useful for measuring force in biological cell micromanipulation processes such as injection of the mouse oocyte/embryo.
Fatemeh Karimirad; Sunita Chauhan; Bijan Shirinzadeh
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-12-14
Journal Detail:
Title:  Journal of biomechanics     Volume:  -     ISSN:  1873-2380     ISO Abbreviation:  J Biomech     Publication Date:  2013 Dec 
Date Detail:
Created Date:  2014-1-13     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0157375     Medline TA:  J Biomech     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2013 Elsevier Ltd. All rights reserved.
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