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Deep learning for automatic cell detection in wide-field microscopy zebrafish images | IEEE Conference Publication | IEEE Xplore

Deep learning for automatic cell detection in wide-field microscopy zebrafish images


Abstract:

The zebrafish has become a popular experimental model organism for biomedical research. In this paper, a unique framework is proposed for automatically detecting Tyrosine...Show More

Abstract:

The zebrafish has become a popular experimental model organism for biomedical research. In this paper, a unique framework is proposed for automatically detecting Tyrosine Hydroxylase-containing (TH-labeled) cells in larval zebrafish brain z-stack images recorded through the wide-field microscope. In this framework, a supervised max-pooling Convolutional Neural Network (CNN) is trained to detect cell pixels in regions that are preselected by a Support Vector Machine (SVM) classifier. The results show that the proposed deep-learned method outperforms hand-crafted techniques and demonstrate its potential for automatic cell detection in wide-field microscopy z-stack zebrafish images.
Date of Conference: 16-19 April 2015
Date Added to IEEE Xplore: 23 July 2015
Electronic ISBN:978-1-4799-2374-8

ISSN Information:

Conference Location: Brooklyn, NY, USA

References

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