Development of biomedical corpus enlargement platform using BERT for bio-entity recognition
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Publication Details
Author list: Phongwattana T., Chan J.H.
Publisher: Hindawi
Publication year: 2019
Volume number: 11953 LNCS
Start page: 454
End page: 463
Number of pages: 10
ISBN: 9781450362313
ISSN: 0146-9428
eISSN: 1745-4557
Languages: English-Great Britain (EN-GB)
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Abstract
Pyricularia Oryzae is a type of fungal spores which can lead to the most damaging rice blast disease. We have developed a quick and robust tool for counting the number of spores for measuring spore concentration using image processing techniques. The image is first thresholded using auto-Otsu's thresholding and adaptive Gaussian threshold. Morphological operations are employed to reduce some noise. With elongated shape of the spore, region properties are considered in the counting process. Our proposed technique is evaluated on 10x and 40x image sets using statistical measures; it outperforms the previous techniques and can be used for early disease diagnosis and further studying spore-related factors. ฉ 2019 Association for Computing Machinery.
Keywords
Image processing, Rice blast disease, Spore counting, Thresholding
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