scholarly journals MyoCount: a software tool for the automated quantification of myotube surface area and nuclear fusion index

2019 ◽  
Vol 4 ◽  
pp. 6 ◽  
Author(s):  
David P. Murphy ◽  
Thomas Nicholson ◽  
Simon W. Jones ◽  
Mary F. O'Leary
Keyword(s):  
Surface Area ◽  
Nuclear Fusion ◽  
Software Tool ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Source Program ◽  
Automated Quantification ◽  
The Mean ◽  
Imagej Software ◽  
Fusion Index

It is often desirable to characterise the morphology of myogenic cultures. To achieve this, the surface area of myotubes is often quantified, along with the nuclear fusion index (NFI). Existing methods of such quantification are time-consuming and subject to error-prone human input. We have developed MyoCount, an open-source program that runs via the freely available MATLAB Runtime and quantifies myotube surface area and NFI. MyoCount allows the user to adjust its parameters to account for differences in image quality, magnification and the colour channels used in generating the image. MyoCount measures of myotube surface area and NFI were compared to the mean of measures performed by two blinded investigators using ImageJ software (surface area R2 = 0.89, NFI R2 =0.87). For NFI, the mean coefficient of variation (CV) between two investigators (17.6 ± 2.3%) was significantly higher than that between the investigator mean and MyoCount (13.5 ± 1.4%). For measurements of myotube area, the CV did not differ between both analysis methods. Given these results and the advantages of applying the same image analysis method uniformly across all images in an experiment, we suggest that MyoCount will be a useful research tool and we publish its source code and instructions for its use alongside this article.

scholarly journals COMPARISON OF EYELID ANGLE MEASURED USING MANUAL AND DIGITAL IMAGE ANALYSIS METHOD

2021 ◽  
Author(s):  
Shravya N ◽  
Swetha Ravichandran ◽  
Rinu Thomas
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Palpebral Fissure ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Interpupillary Distance ◽  
Significant Difference ◽  
The Mean ◽  
Imagej Software

Aim: To compare the eyelid angle measured by using a manual method (Using protractor) and digital image analysis method (Using ImageJ software) at different distances of eye gaze. Methodology: This prospective cross-sectional study was conducted in the preclinical lab at Manipal College of Health Professions. Subjects with no eyelid abnormalities were included in the study and they were asked to fixate at different distances a) at 3 metre (Distance gaze) b) at 70 cm (Intermediategaze) and c) at 40 cm(Near gaze). Using a protractor, the eyelid angle measurements were repeated at various distances which comprised the manual measurement. In the image analysis method, images were captured during distance, intermediate and near gaze using smartphone placed on theside of the face. These images were then analysed using ImageJ software for determining eyelid angle using image analysis method. Palpebral fissure height, Palpebral fissure width, Interpupillary distance, Intercanthal width, Binocular width, Height of open upper lid were some additional anthropometry measurements that were done using meter scale and PD ruler. Results: The mean age of the participants was 20±0.5 years. Anthropometry measurements of the eyelid and Palpebral fissure were done using meter scaleand PD ruler. The mean and standard deviation of the measured parametersare as follows Interpupillary distance: 60.95±2.37 mm, Endo Inter canthal distance: 32.20±2.39 mm, Exo Inter cantal distance: 95.50±3.80 mm, Palpebralfissure height_OD: 12.11±1.32 mm, Palpebral fissure height_OS:12.16±1.46mm, PFW_OD: 32.00±1.10 mm, PFW_OS: 32.11±1.24 mm, Height of upper eyelids_OD: 10.26±1.66 mm and Height of upper eyelids_OS:10.42±1.83 mm. In the right eye, there was no statistically significant difference (p>0.05) between manual protractor method and digital image analysismethod at distance but there was a statistically significant difference (p<0.05)between manual protractor method and digital image analysis method atIntermediate and near. In left eye, there was statistically significant difference(p<0.05) between manual protractor method and digital image analysis method at all three distances. Conclusion: There is a significant difference in eyelid angle measured using manual protractor method and digital image analysis method. The measurement of eyelid angle serves as a critical reference point during cosmetic and reconstructive surgical interventions of the eyelid and accurate measurements are essential for preoperative assessment, surgical planning and postoperative evaluation. Hence more studies on the validation of the anthropometry measurements and eyelid angle using digital image analysis areessential to use digital image analysis in routine eye care practice.

A study of using a simple 2D image analysis method to monitor the surface area of hypertrophic scars on hand during pressure therapy

Burns ◽  
2020 ◽  
Vol 46 (7) ◽  
pp. 1548-1555
Author(s):  
Annie Yu ◽  
Kit Lun Yick ◽  
Sun Pui Ng ◽  
Joanne Yip ◽  
Ying Fan Chan
Keyword(s):  
Image Analysis ◽  
Surface Area ◽  
Hypertrophic Scars ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Pressure Therapy

Rapid determination of histamine in fish by thin-layer chromatography-image analysis method using diazotized visualization reagent prepared withp-nitroaniline

2018 ◽  
Vol 10 (27) ◽  
pp. 3386-3392 ◽  
Author(s):  
Hui Yu ◽  
Daina Zhuang ◽  
Xingjuan Hu ◽  
Shuang Zhang ◽  
Zhiyong He ◽  
...  
Keyword(s):  
Image Analysis ◽  
Thin Layer ◽  
Thin Layer Chromatography ◽  
Analytical Method ◽  
Rapid Determination ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Imagej Software ◽  
Layer Chromatography

A novel analytical method for rapid determination of histamine in fish involves methanol extraction, manual spotting, thin-layer chromatography (TLC) for less than 15 min, visualization by diazotizedp-nitroaniline reagent, and quantitation by image analysis using the ImageJ software.

An Image Analysis Method for Studing Yarn Cross-Sectional Structure

2011 ◽  
Vol 301-303 ◽  
pp. 41-44
Author(s):  
Huang Zhen ◽  
Kun Yang
Keyword(s):  
Image Analysis ◽  
Cross Section ◽  
Binary Operation ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Cross Sectional ◽  
Equal Area ◽  
Fiber Area ◽  
Imagej Software ◽  
Sectional Structure

In this paper, we propose an analysis method for examining yarn cross-sectional structure. After obtaing yarn cross section photos, annular equal area yarn model and binary operation were used for image analysis and treatment. Then, statistic method was applied to analyze the distribution of fiber area in equal areas. The centroid position of the fiber and yarn were calculated, and the percentage values of the fiber area in each equal division against its circle (ring) area were obtained by using an ImageJ software. Finally a yarn sample was examined, and results show that this method is useful.

Automated measurement of size and visibility of small inclusions in HREM images

1995 ◽  
Vol 53 ◽  
pp. 648-649
Author(s):  
S. Paciornik ◽  
S.Q. Xiao ◽  
S. Hinderberger ◽  
E. Johnson ◽  
U. Dahmen
Keyword(s):  
Apparent Size ◽  
Intensity Difference ◽  
Automatic Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
First Line ◽  
Low Visibility ◽  
The Matrix ◽  
Intensity Changes ◽  
The Mean

This work describes an automatic image analysis method for measuring the visibility and apparent size of inclusions in a matrix, imaged by HREM. The method is based on intensity changes between the matrix and inclusion regions of the image. It provides a quantitative way of describing changes that are generally interpreted only in a qualitative sense. It also allows for measurements in situations of very low visibility where visual estimates are nearly impossible. The method measures the mean squared intensity difference between lines of an image defined asR = mean [(Im(x) - Im(x0))2]Im(x) is a line, selected by the user, which is scanned across the image. Im(x0) is the first line of the scan, taken in a region away from the inclusion. For each position of Im(x), Im(x0) is subtracted pixel by pixel, and the average of all squared intensity differences, is obtained (R).As the line is scanned across the image, R will oscillate with a period given by the lattice spacing along the scan direction.

Voronoi Analysis of a Soccer Game

2004 ◽  
Vol 9 (3) ◽  
pp. 233-240 ◽  
Author(s):  
S. Kim
Keyword(s):  
Collective Behavior ◽  
Quantitative Assessment ◽  
The Other ◽  
Analysis Method ◽  
Random System ◽  
Soccer Game ◽  
Voronoi Polygons ◽  
The Mean

This paper describes a Voronoi analysis method to analyze a soccer game. It is important for us to know the quantitative assessment of contribution done by a player or a team in the game as an individual or collective behavior. The mean numbers of vertices are reported to be 5–6, which is a little less than those of a perfect random system. Voronoi polygons areas can be used in evaluating the dominance of a team over the other. By introducing an excess Voronoi area, we can draw some fruitful results to appraise a player or a team rather quantitatively.

scholarly journals Automated image analysis method for oil-release test of lipid-based materials

MethodsX ◽  
2021 ◽  
pp. 101447
Author(s):  
Fabio Valoppi ◽  
Petri Lassila ◽  
Ari Salmi ◽  
Edward Haeggström
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Release Test

scholarly journals Quantification and Comparison of Talar Exposure Utilizing a Posteromedial Approach and Medial Malleolar Osteotomy

2021 ◽  
Vol 6 (2) ◽  
pp. 247301142110126
Author(s):  
Jeffrey Donahue ◽  
Ademola Shofoluwe ◽  
Kurt Krautmann ◽  
Emilio Grau-Cruz ◽  
Stephen Becher ◽  
...  
Keyword(s):  
Surface Area ◽  
Digital Image ◽  
National Institutes Of Health ◽  
Level Of Evidence ◽  
Posterior Process ◽  
Medial Malleolar Osteotomy ◽  
Fresh Frozen ◽  
Average Quantity ◽  
Operative Fixation ◽  
Imagej Software

Background: Fractures of the talus are a rare but challenging injury. This study sought to quantify the area of osseous exposure afforded by a posteromedial approach to the talus and medial malleolar osteotomy. Methods: Five fresh-frozen cadaveric lower extremities were dissected using a posteromedial approach and medial malleolar osteotomy respectively. Following exposure, the talar surfaces directedly visualized were marked and captured using a calibrated digital image. The digital images were then analyzed using ImageJ software (National Institutes of Health) to calculate the surface area of the exposure. Results: The average square area of talus exposed using the posteromedial approach was 9.70 cm2 (SD = 2.20, range 7.20-12.46). The average quantity of talar exposure expressed as a percentage was 9% (SD = 1.58, range 7.03-10.40). The average square area of talus exposed using a medial malleolar osteotomy was 14.32 cm2 (SD = 2.00, range 11.26-16.66). The average quantity of talar exposure expressed as a percentage was 12.94% (SD = 1.79, range 9.97-14.73). The posteromedial approach provided superior visualization of the posterior talus, whereas the medial malleolar osteotomy offered greater access to the medial body. Conclusion: The posteromedial approach and medial malleolar osteotomy allow for significant exposure of the talus, yielding 9.70 and 14.32 cm2, respectively. Given the differing portions of the talus exposed, surgeons may prefer to use the posteromedial approach for operative fixation of posterior process fractures and elect to use a medial malleolar osteotomy in cases requiring more extensive medial and distal exposure for neck or neck/body fractures. Level of Evidence: Level IV.

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