scholarly journals Erratum to “Development of a Rapid and Precise Method of Digital Image Analysis to Quantify Canopy Density and Structural Complexity”

2017 ◽  
Vol 2017 ◽  
pp. 1-1
Author(s):  
Anne E. Goodenough ◽  
Andrew S. Goodenough
ISRN Ecology ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Anne E. Goodenough ◽  
Andrew S. Goodenough

Estimation of canopy density is necessary for ecological research and woodland management. However, traditional manual methods are time consuming and subject to interobserver variability, while existing photographic methods usually require expensive fish-eye lenses and complex analysis. Here we introduce and test a new method of digital image analysis, CanopyDigi. This allows user-defined threshold to polarise the 256 grey shades of a standard monochrome bitmap into dark “canopy” and light “sky” pixels (the threshold being selected using false-colour images to ensure its suitability). Canopy density data are calculated automatically and rapidly, and, unlike many other common methods, aggregation data are obtainable using Morisita’s index to differentiate closed (diffuse light) and open (direct light) canopies. Results were highly repeatable in both homogeneous and heterogeneous woodland. Estimates correlated strongly with existing (nondigital) canopy techniques, but quicker and with significantly lower interobserver variability (CV = 3.74% versus 20.73%). We conclude that our new method is an inexpensive and precise technique for quantifying canopy density and aggregation.


2000 ◽  
Vol 10 (2) ◽  
pp. 7-9
Author(s):  
Yaser Natour ◽  
Christine Sapienza ◽  
Mark Schmalz ◽  
Savita Collins

2019 ◽  
Vol 8 (3) ◽  
pp. 11 ◽  
Author(s):  
Gustav Stålhammar ◽  
Thonnie Rose O. See ◽  
Stephen Phillips ◽  
Stefan Seregard ◽  
Hans E. Grossniklaus

2008 ◽  
Vol 14 (2) ◽  
pp. 192-200 ◽  
Author(s):  
Hiromasa Tanaka ◽  
Gojiro Nakagami ◽  
Hiromi Sanada ◽  
Yunita Sari ◽  
Hiroshi Kobayashi ◽  
...  

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Aristeidis A. Villias ◽  
Stefanos G. Kourtis ◽  
Hercules C. Karkazis ◽  
Gregory L. Polyzois

Abstract Background The replica technique with its modifications (negative replica) has been used for the assessment of marginal fit (MF). However, identification of the boundaries between prosthesis, cement, and abutment is challenging. The recently developed Digital Image Analysis Sequence (DIAS) addresses this limitation. Although DIAS is applicable, its reliability has not yet been proven. The purpose of this study was to verify the DIAS as an acceptable method for the quantitative assessment of MF at cemented crowns, by conducting statistical tests of agreement between different examiners. Methods One hundred fifty-one implant-supported experimental crowns were cemented. Equal negative replicas were produced from the assemblies. Each replica was sectioned in six parts, which were photographed under an optical microscope. From the 906 standardized digital photomicrographs (0.65 μm/pixel), 130 were randomly selected for analysis. DIAS included tracing the profile of the crown and the abutment and marking the margin definition points before cementation. Next, the traced and marked outlines were superimposed on each digital image, highlighting the components’ boundaries and enabling MF measurements. One researcher ran the analysis twice and three others once, independently. Five groups of 130 measurements were formed. Intra- and interobserver reliability was evaluated with intraclass correlation coefficient (ICC). Agreement was estimated with the standard error of measurement (SEM), the smallest detectable change at the 95% confidence level (SDC95%), and the Bland and Altman method of limits of agreement (LoA). Results Measured MF ranged between 22.83 and 286.58 pixels. Both the intra- and interobserver reliability were excellent, ICC = 1 at 95% confidence level. The intra- and interobserver SEM and SDC95% were less than 1 and 3 pixels, respectively. The Bland–Altman analysis presented graphically high level of agreement between the mean measurement of the first observer and each of the three other observers’ measurements. Differences between observers were normally distributed. In all three cases, the mean difference was less than 1 pixel and within ± 3 pixels LoA laid at least 95% of differences. T tests of the differences did not reveal any fixed bias (P > .05, not significant). Conclusion The DIAS is an objective and reliable method able to detect and quantify MF at ranges observed in clinical practice.


1998 ◽  
Vol 7 (5) ◽  
pp. 469-478 ◽  
Author(s):  
Jan P. Stegemann ◽  
John J. O'Neil ◽  
Don T. Nicholson ◽  
Claudy J.-P. Mullon

Accurate and consistent measurement of tissue volume is critical to performing many types of islet research; however, conventional visual determination of isolated islet yields through a microscope is heavily operator dependent. An improved method of islet volume determination using digital image analysis (DIA) was developed to remove operator bias and automate the islet counting process. A series of 140 porcine islet isolations were used to evaluate the DIA method in three separate stages. In Stage 1 ( n = 29 isolations), the conventional and DIA methods were correlated with two other independent islet quantitation methods: insulin extraction, and DNA extraction. It was found that volumes determined by DIA correlated more closely with insulin content and DNA content than did conventionally determined volumes. In Stages 2 and 3 ( n = 54 and 57 isolations, respectively), it was shown that an increase in the number of fields analyzed by DIA did not significantly improve the quality of the correlations. Inclusion of very small tissue (<50 fun in diameter), which is ignored in the conventional protocol affected yields by less than 10% and did not significantly improve the correlation with insulin or DNA content. Quantitation of isolated islet tissue volume using DIA has been shown to be rapid, consistent, and objective. In the laboratory, use of this method as the standard for islet volume measurement will allow more meaningful comparison of experimental results between centers. In the clinic, its use will allow more accurate dosing of transplanted tissue. © 1998 Elsevier Science Inc.


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