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16 July 2019 Vision based evaluation of the contamination level in high resolution images for industrial and clinical quality control applications
Aurélien Launay, Guillaume Perrin, Ernest Hirsch
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Proceedings Volume 11172, Fourteenth International Conference on Quality Control by Artificial Vision; 1117204 (2019) https://doi.org/10.1117/12.2521442
Event: Fourteenth International Conference on Quality Control by Artificial Vision, 2019, Mulhouse, France
Abstract
In clinical environments and pharmaceutical industrial productions, early detection of contamination by microorganisms is a key point in terms of quality control. Determination of such contaminations relies on cultures in Petri dishes, the observation of which, through the detection of colonies of microorganisms, leads to methods enabling their determinations. However, these methods show limits in terms of speed and are rather tedious. To overcome these shortcomings, a method based on image analysis and deep learning is proposed to improve both detection of microorganism colonies in Petri dishes and quality of the quantitative determination of the contamination levels.
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Aurélien Launay, Guillaume Perrin, and Ernest Hirsch "Vision based evaluation of the contamination level in high resolution images for industrial and clinical quality control applications", Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 1117204 (16 July 2019); https://doi.org/10.1117/12.2521442
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KEYWORDS
Contamination
Image analysis
Microbiology
Neural networks
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