{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Lin Q"],"funding":["National Keypoint Research and Invention Program in 13th Five-Year, China"],"pagination":["e0235727"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7500654"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(9)"],"pubmed_abstract":["The objective of this study was to develop a computer-aided method to quantify the obvious degree of growth ring boundaries of softwood species, based on data analysis with some image processing technologies. For this purpose, a 5× magnified cross-section color micro-image of softwood was cropped into 20 sub-images, and then every image was binarized as a gray image according to an automatic threshold value. After that, the number of black pixels in the gray image was counted row by row and the number of black pixels was binarized to 0 or 100. Finally, a transition band from earlywood to latewood on the sub-image was identified. If everything goes as planned, the growth ring boundaries of the sub-image would be distinct. Otherwise would be indistinct or absent. If more than 50% sub-images "],"journal":["PloS one"],"pubmed_title":["A computer-aided method for identifying the presence of softwood growth ring boundaries."],"pmcid":["PMC7500654"],"funding_grant_id":["2016YFD0600702"],"pubmed_authors":["Qiu J","Lin Q","He T","He X","Sun Y"],"additional_accession":[]},"is_claimable":false,"name":"A computer-aided method for identifying the presence of softwood growth ring boundaries.","description":"The objective of this study was to develop a computer-aided method to quantify the obvious degree of growth ring boundaries of softwood species, based on data analysis with some image processing technologies. For this purpose, a 5× magnified cross-section color micro-image of softwood was cropped into 20 sub-images, and then every image was binarized as a gray image according to an automatic threshold value. After that, the number of black pixels in the gray image was counted row by row and the number of black pixels was binarized to 0 or 100. Finally, a transition band from earlywood to latewood on the sub-image was identified. If everything goes as planned, the growth ring boundaries of the sub-image would be distinct. Otherwise would be indistinct or absent. If more than 50% sub-images ","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020","modification":"2025-04-21T15:36:22.977Z","creation":"2020-09-30T07:04:05Z"},"accession":"S-EPMC7500654","cross_references":{"pubmed":["32946443"],"doi":["10.1371/journal.pone.0235727"]}}