Shading Correction Methods for Digital Image Analysis of Confocal Wood Images

IAWA Journal ◽  
2007 ◽  
Vol 28 (3) ◽  
pp. 349-364 ◽  
Author(s):  
Mattias K. Moëll ◽  
Lloyd A. Donaldson
Keyword(s):  
Cell Wall ◽  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Sample Surface ◽  
Field Of View ◽  
Wall Area ◽  
Cell Dimensions ◽  
Confocal Fluorescence ◽  
Imaging Plane

Confocal fluorescence microscopy provides a rapid method for acquiring high quality optically thin section images of wood suitable for measurement of cell dimensions. Single optical slice images of wood may occasionally contain artefacts due to differential light absorption caused by variation in the distance between the sample surface and the imaging plane across the field of view. Regional brightness variations, which we call shading, may cause problems when such images are used for wood cell measurements using digital image analysis, affecting the accuracy of wood cell dimensions. We have compared various shading correction methods for confocal microscope images and investigated the effect of shading on both the c1assification of cell wall pixels and the resulting cell dimension measurements. Severe shading results in significant errors for measurement of cell wall area, but smaller errors for cell wall thickness and lumen diameter. Some shading correction methods have unwanted effects on pixel c1assification and cell dimensions, while more effective methods remove the shading without introducing further artefacts. The effect of shading is influenced by choice of thresholding method.

COMPARISON OF SEGMENTATION METHODS FOR DIGITAL IMAGE ANALYSIS OF CONFOCAL MICROSCOPE IMAGES TO MEASURE TRACHEID CELL DIMENSIONS

IAWA Journal ◽  
2001 ◽  
Vol 22 (3) ◽  
pp. 267-288 ◽  
Author(s):  
Mattias K. Moëll ◽  
Lloyd A. Donaldson
Keyword(s):  
Cell Wall ◽  
Image Analysis ◽  
Digital Image ◽  
Automatic Segmentation ◽  
Transverse Cross Section ◽  
Confocal Microscope ◽  
Segmentation Method ◽  
Segmentation Methods ◽  
Cell Dimensions ◽  
Microscope Images

Image analysis is a common tool for measuring tracheid cell dimensions. When analyzing a digital image of a transverse cross section of wood, one of the initial procedures is that of segmentation. This involves classifying a picture element (pixel) as either cell wall or lumen. The accuracy of tracheid measurements is dependent on how well the result of the segmentation procedure corresponds to the true distributions of cell wall or lumen pixels. In this paper a comparison of segmentation methods is given. The effect of segmentation method on measurements is investigated and the performance of each method is discussed.We demonstrate that automated segmentation methods remove observer bias and are thus capable of more reproducible results. The contrast for confocal microscope images is of such quality that one of the fastest and simplest automatic segmentation methods may be used.

Digital Image Analysis of the Larynx

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

scholarly journals Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis

2019 ◽  
Vol 8 (3) ◽  
pp. 11 ◽  
Author(s):  
Gustav Stålhammar ◽  
Thonnie Rose O. See ◽  
Stephen Phillips ◽  
Stefan Seregard ◽  
Hans E. Grossniklaus
Keyword(s):  
Image Analysis ◽  
Uveal Melanoma ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Melanoma Metastasis

Quantitative evaluation of elderly skin based on digital image analysis

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

scholarly journals In vitro validation of Digital Image Analysis Sequence (DIAS) for the assessment of the marginal fit of cement-retained implant-supported experimental crowns

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Aristeidis A. Villias ◽  
Stefanos G. Kourtis ◽  
Hercules C. Karkazis ◽  
Gregory L. Polyzois
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Confidence Level ◽  
Digital Image Analysis ◽  
Statistical Tests ◽  
Interobserver Reliability ◽  
Intraclass Correlation ◽  
Marginal Fit ◽  
Smallest Detectable Change ◽  
The Mean

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.

Improved Assessment of Isolated Islet Tissue Volume Using Digital Image Analysis

1998 ◽  
Vol 7 (5) ◽  
pp. 469-478 ◽  
Author(s):  
Jan P. Stegemann ◽  
John J. O'Neil ◽  
Don T. Nicholson ◽  
Claudy J.-P. Mullon
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Dna Content ◽  
Digital Image Analysis ◽  
Volume Measurement ◽  
Volume Determination ◽  
Tissue Volume ◽  
Porcine Islet ◽  
Islet Volume ◽  
Islet Tissue

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.

Sign in / Sign up

Export Citation Format

Share Document