Dipak Mahatara , Filipe Campelo , Laurent Houle , Alain Caron , Julie Barrette , Pierre Francus , Robert Schneider
{"title":"CTRing:从圆盘和原木的计算机断层扫描图像中提取木材密度剖面的 R 软件包","authors":"Dipak Mahatara , Filipe Campelo , Laurent Houle , Alain Caron , Julie Barrette , Pierre Francus , Robert Schneider","doi":"10.1016/j.dendro.2024.126274","DOIUrl":null,"url":null,"abstract":"<div><div>Accurately determining the position of pith and accessing tree-ring density profiles, including intra-ring variations, is important for both the forest industry and dendroclimatology. Although several available methods exist for acquiring this information, such as X-ray computed tomography (CT), micro-CT, and X-ray films, the availability of open-source programs for extracting data remains limited. The CTRing package in the R environment integrates a series of functions to detect precisely the pith and tree-ring boundaries and generate tree-ring density profiles using CT images of tree cross sections. Before processing, grey values are transformed into density using a calibration function. Pith position is then detected by combining an adapted Hough Transform method and a one-dimensional edge detector. Tree-ring profiles along the pith-to-bark path of interest are inspected visually, and tree-ring boundaries can be easily added or removed manually via a graphical user interface. After correcting for tree-ring boundaries, the inflection points of a 3rd-degree polynomial obtained from density profiles are used to delimit the earlywood–latewood transition. We tested this package using 60 CT-scanned images of white spruce (<em>Picea glauca</em> (Moench) Voss) discs collected at various tree heights (0 %, 25 %, 50 % and 75 % of the total tree height as well as at 1.3 m). The pith detection function had an average mean error of 0.72 mm with 95 % of the automatically detected pith locations that differed by less than 2 mm from their manually located positions. Error decreased toward the apex of the tree. The functions of the CTRing package are flexible and can be easily implemented or adapted. The package could also be used with simple images of discs to obtain ring-width time series; however, this use must be evaluated further. Future work with this package involves assessing the use of low-quality images and ring-porous species.</div></div>","PeriodicalId":50595,"journal":{"name":"Dendrochronologia","volume":"88 ","pages":"Article 126274"},"PeriodicalIF":2.7000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CTRing: An R package to extract wood density profiles from computed tomography images of discs and logs\",\"authors\":\"Dipak Mahatara , Filipe Campelo , Laurent Houle , Alain Caron , Julie Barrette , Pierre Francus , Robert Schneider\",\"doi\":\"10.1016/j.dendro.2024.126274\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Accurately determining the position of pith and accessing tree-ring density profiles, including intra-ring variations, is important for both the forest industry and dendroclimatology. Although several available methods exist for acquiring this information, such as X-ray computed tomography (CT), micro-CT, and X-ray films, the availability of open-source programs for extracting data remains limited. The CTRing package in the R environment integrates a series of functions to detect precisely the pith and tree-ring boundaries and generate tree-ring density profiles using CT images of tree cross sections. Before processing, grey values are transformed into density using a calibration function. Pith position is then detected by combining an adapted Hough Transform method and a one-dimensional edge detector. Tree-ring profiles along the pith-to-bark path of interest are inspected visually, and tree-ring boundaries can be easily added or removed manually via a graphical user interface. After correcting for tree-ring boundaries, the inflection points of a 3rd-degree polynomial obtained from density profiles are used to delimit the earlywood–latewood transition. We tested this package using 60 CT-scanned images of white spruce (<em>Picea glauca</em> (Moench) Voss) discs collected at various tree heights (0 %, 25 %, 50 % and 75 % of the total tree height as well as at 1.3 m). The pith detection function had an average mean error of 0.72 mm with 95 % of the automatically detected pith locations that differed by less than 2 mm from their manually located positions. Error decreased toward the apex of the tree. The functions of the CTRing package are flexible and can be easily implemented or adapted. The package could also be used with simple images of discs to obtain ring-width time series; however, this use must be evaluated further. 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CTRing: An R package to extract wood density profiles from computed tomography images of discs and logs
Accurately determining the position of pith and accessing tree-ring density profiles, including intra-ring variations, is important for both the forest industry and dendroclimatology. Although several available methods exist for acquiring this information, such as X-ray computed tomography (CT), micro-CT, and X-ray films, the availability of open-source programs for extracting data remains limited. The CTRing package in the R environment integrates a series of functions to detect precisely the pith and tree-ring boundaries and generate tree-ring density profiles using CT images of tree cross sections. Before processing, grey values are transformed into density using a calibration function. Pith position is then detected by combining an adapted Hough Transform method and a one-dimensional edge detector. Tree-ring profiles along the pith-to-bark path of interest are inspected visually, and tree-ring boundaries can be easily added or removed manually via a graphical user interface. After correcting for tree-ring boundaries, the inflection points of a 3rd-degree polynomial obtained from density profiles are used to delimit the earlywood–latewood transition. We tested this package using 60 CT-scanned images of white spruce (Picea glauca (Moench) Voss) discs collected at various tree heights (0 %, 25 %, 50 % and 75 % of the total tree height as well as at 1.3 m). The pith detection function had an average mean error of 0.72 mm with 95 % of the automatically detected pith locations that differed by less than 2 mm from their manually located positions. Error decreased toward the apex of the tree. The functions of the CTRing package are flexible and can be easily implemented or adapted. The package could also be used with simple images of discs to obtain ring-width time series; however, this use must be evaluated further. Future work with this package involves assessing the use of low-quality images and ring-porous species.
期刊介绍:
Dendrochronologia is a peer-reviewed international scholarly journal that presents high-quality research related to growth rings of woody plants, i.e., trees and shrubs, and the application of tree-ring studies.
The areas covered by the journal include, but are not limited to:
Archaeology
Botany
Climatology
Ecology
Forestry
Geology
Hydrology
Original research articles, reviews, communications, technical notes and personal notes are considered for publication.