scholarly journals High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection

PLoS ONE ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. e0148469 ◽  
Author(s):  
Priya Choudhry
Keyword(s):  
Image Analysis ◽  
Edge Detection ◽  
High Throughput ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Cell Counting ◽  
High Throughput Method

Quantification of gap junctional intercellular communication based on digital image analysis

2009 ◽  
Vol 297 (2) ◽  
pp. R243-R247 ◽  
Author(s):  
Johannes P. Hofgaard ◽  
Sarah Mollerup ◽  
Niels-Henrik Holstein-Rathlou ◽  
Morten Schak Nielsen
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Intercellular Communication ◽  
Connexin 43 ◽  
Digital Image Analysis ◽  
Fluorescent Dyes ◽  
Cell Counting ◽  
C6 Glioma Cells ◽  
Gap Junctional Intercellular Communication ◽  
Metabolic Coupling

Intercellular communication via gap junction channels can be quantified by several methods based on diffusion of fluorescent dyes or metabolites. Given the variation in intercellular coupling of cells, even under untreated control conditions, it is of essence to quantify the coupling between numerous cells to obtain reliable estimates of metabolic coupling. Quantification is often based on manual counting of fluorescent cells, which is time consuming and may include some degree of subjectivity. In this report, we introduce a technique based on digital image analysis, and the software for the analysis is presented together with a detailed protocol in the online supplemental material ( http://bmi.ku.dk/matlab_program/ ). Fluorescent dye was introduced in connexin 43-expressing C6 glioma cells by in situ electroporation, and fluorescence intensity was measured in the electroporated cells and in cells receiving dye by intercellular diffusion. The analysis performed is semiautomatic, and comparison with traditional cell counting shows that this method reliably determines the effect of uncoupling by several interventions. This new method of analysis yields a rapid and objective quantification process with a high degree of reproducibility.

scholarly journals Measuring Quantitative Virulence in the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis

2014 ◽  
Vol 104 (9) ◽  
pp. 985-992 ◽  
Author(s):  
Ethan L. Stewart ◽  
Bruce A. McDonald
Keyword(s):  
Image Analysis ◽  
High Throughput ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Continuous Distribution ◽  
Automated Image Analysis ◽  
Host Specialization ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Zymoseptoria Tritici

Zymoseptoria tritici, causal agent of Septoria tritici blotch on wheat, produces pycnidia in chlorotic and necrotic lesions on infected leaves. A high-throughput phenotyping method was developed based on automated digital image analysis that accurately measures the percentage of leaf area covered by lesions (PLACL) as well as pycnidia size and number. A seedling inoculation assay was conducted using 361 Z. tritici isolates originating from a controlled cross and two different winter wheat cultivars. Pycnidia size and density were found to be quantitative traits that showed a continuous distribution in the progeny. There was a weak correlation between pycnidia density and size (r = −0.27) and between pycnidia density and PLACL (r = 0.37). There were significant differences in PLACL and pycnidia density on resistant and susceptible cultivars. In all, >20% of the offspring exhibited significantly different pycnidia density on the two cultivars, consistent with host specialization. Automated image analysis provided greater accuracy and precision compared with traditional visual estimates of virulence. These results show that digital image analysis provides a powerful tool for measuring differences in quantitative virulence among strains of Z. tritici.

scholarly journals High-Throughput Phenotyping of Seed/Seedling Evaluation Using Digital Image Analysis

Agronomy ◽  
2018 ◽  
Vol 8 (5) ◽  
pp. 63 ◽  
Author(s):  
Chongyuan Zhang ◽  
Yongsheng Si ◽  
Jacob Lamkey ◽  
Rick Boydston ◽  
Kimberly Garland-Campbell ◽  
...  
Keyword(s):  
Image Analysis ◽  
High Throughput ◽  
Digital Image ◽  
Digital Image Analysis ◽  
High Throughput Phenotyping

scholarly journals RADIX: rhizoslide platform allowing high throughput digital image analysis of root system expansion

Plant Methods ◽  
2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Chantal Le Marié ◽  
Norbert Kirchgessner ◽  
Patrick Flütsch ◽  
Johannes Pfeifer ◽  
Achim Walter ◽  
...  
Keyword(s):  
Image Analysis ◽  
Root System ◽  
High Throughput ◽  
Digital Image ◽  
Digital Image Analysis ◽  
System Expansion

Quantitative digital image analysis of chromogenic assays for high throughput screening of α-amylase mutant libraries

2009 ◽  
Vol 31 (8) ◽  
pp. 1197-1201 ◽  
Author(s):  
Manoharan Shankar ◽  
Ramachandran Priyadharshini ◽  
Paramasamy Gunasekaran
Keyword(s):  
Image Analysis ◽  
High Throughput ◽  
Digital Image ◽  
High Throughput Screening ◽  
Digital Image Analysis

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
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