Pebrine diagnosis using quantitative phase imaging and machine learning

Prasobhkumar, PP and Venukumar, A and Francis, CR and Gorthi, SS (2021) Pebrine diagnosis using quantitative phase imaging and machine learning. In: Journal of Biophotonics .

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Abstract

Pebrine is the most dreaded infectious disease of the silkworm and has devastated sericulture in Europe during the 18th century. Thereafter, if it is detected, the crop is burned to prevent further dissemination. The conventional microscopic examination of moth's body fluid is erroneous and it exacerbates on Metarhizium anisopliae (MA) contaminated test samples. This is due to the resemblance of pebrine and MA spores in the microscopic examination. Therefore, this study aims to demonstrate an efficient pebrine detection technique. In the proposed method, a motorised brightfield microscope is custom-made to acquire focused and defocused images of test spores. These images are used to produce quantitative phase images of the spores by the transport of intensity equation method. The phase images' histogram of oriented gradients feature is used by a machine learning classifier to categorise the spores. This system classified 92 pebrine and 185 MA spores with an accuracy of 97 at 0.04 seconds/spore. The duration taken for image acquisition is 2.5 minutes per sample (10 fields of view covering an area of 302 � 260 μm2). The proposed method shows reliable results in pebrine diagnosis and would be an efficient alternative for current approaches. © 2021 Wiley-VCH GmbH

Item Type:	Journal Article
Publication:	Journal of Biophotonics
Publisher:	John Wiley and Sons Inc
Additional Information:	The copyright for this article belongs to John Wiley and Sons Inc
Keywords:	Body fluids; Diagnosis; Machine learning; Microscopic examination; Turing machines, 18th century; Fields of views; Histogram of oriented gradients; Infectious disease; Metarhizium anisopliae; Quantitative phase imaging; Reliable results; Transport of intensity equations, Image acquisition
Department/Centre:	Division of Physical & Mathematical Sciences > Instrumentation Appiled Physics
Date Deposited:	05 Aug 2021 10:43
Last Modified:	05 Aug 2021 10:43
URI:	http://eprints.iisc.ac.in/id/eprint/69062

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