Adopting automated image analysis tool for fibrin network: Can we obtain clot properties for practical application?

2017 ◽  
Vol 39 (5) ◽  
pp. e121-e123 ◽  
Author(s):  
J. G. Yoon ◽  
J. Song
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Tool ◽  
Practical Application ◽  
Fibrin Network

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

scholarly journals Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis

Soft Matter ◽  
2021 ◽  
Author(s):  
Muammer Y. Yaman ◽  
Kathryn N. Guye ◽  
Maxim Ziatdinov ◽  
Hao Shen ◽  
David Baker ◽  
...  
Keyword(s):  
Image Analysis ◽  
De Novo ◽  
Automated Image Analysis ◽  
Analysis Tool ◽  
Au Nanorods

In this study, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates using automated image analysis tool.

Automated image analysis tool to measure microbial growth on solid cultures

2018 ◽  
Vol 151 ◽  
pp. 426-430 ◽  
Author(s):  
Francisco Javier Ancin-Murguzur ◽  
Aitor Barbero-López ◽  
Sari Kontunen-Soppela ◽  
Antti Haapala
Keyword(s):  
Image Analysis ◽  
Microbial Growth ◽  
Automated Image Analysis ◽  
Analysis Tool

scholarly journals Deep learning method for comet segmentation and comet assay image analysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yiyu Hong ◽  
Hyo-Jeong Han ◽  
Hannah Lee ◽  
Donghwan Lee ◽  
Junsu Ko ◽  
...  
Keyword(s):  
Image Analysis ◽  
Deep Learning ◽  
Comet Assay ◽  
Tail Length ◽  
High Sensitivity ◽  
Analysis Tool ◽  
Test Results ◽  
Practical Application ◽  
Average Precision ◽  
The Arts

Abstract Comet assay is a widely used method, especially in the field of genotoxicity, to quantify and measure DNA damage visually at the level of individual cells with high sensitivity and efficiency. Generally, computer programs are used to analyze comet assay output images following two main steps. First, each comet region must be located and segmented, and next, it is scored using common metrics (e.g., tail length and tail moment). Currently, most studies on comet assay image analysis have adopted hand-crafted features rather than the recent and effective deep learning (DL) methods. In this paper, however, we propose a DL-based baseline method, called DeepComet, for comet segmentation. Furthermore, we created a trainable and testable comet assay image dataset that contains 1037 comet assay images with 8271 manually annotated comet objects. From the comet segmentation test results with the proposed dataset, the DeepComet achieves high average precision (AP), which is an essential metric in image segmentation and detection tasks. A comparative analysis was performed between the DeepComet and the state-of-the-arts automatic comet segmentation programs on the dataset. Besides, we found that the DeepComet records high correlations with a commercial comet analysis tool, which suggests that the DeepComet is suitable for practical application.

Automated image analysis tool for migration fat bloom evaluation of chocolate coated food products

LWT ◽  
2008 ◽  
Vol 41 (10) ◽  
pp. 1884-1891 ◽  
Author(s):  
Ingmar Nopens ◽  
Imogen Foubert ◽  
Veerle De Graef ◽  
Delina Van Laere ◽  
Koen Dewettinck ◽  
...  
Keyword(s):  
Image Analysis ◽  
Food Products ◽  
Automated Image Analysis ◽  
Analysis Tool ◽  
Fat Bloom

scholarly journals Quantifying plasticity in vessel grouping – added value from the image analysis tool ROXAS

IAWA Journal ◽  
2013 ◽  
Vol 34 (4) ◽  
pp. 433-445 ◽  
Author(s):  
Georg von Arx ◽  
Christoph Kueffer ◽  
Patrick Fonti
Keyword(s):  
Image Analysis ◽  
Cross Sections ◽  
Automated Image Analysis ◽  
Added Value ◽  
Analysis Tool ◽  
Vessel Size ◽  
Verbascum Thapsus ◽  
High Resolution Images ◽  
High Degree

The functional role of the connectivity of the xylem network, especially the arrangement of solitary and grouped vessels in a cross section, has often been discussed in the literature. Vessel grouping may improve hydraulic integration and increase resilience to cavitation through redundancy of hydraulic pathways. Alternatively, a high degree of hydraulic integration may facilitate the spread of cavitations among neighboring vessels. Here we show how automated image analysis tools such as ROXAS (see www.wsl.ch/roxas) may greatly enhance the capacity for studying vessel grouping while avoiding some methodological limitations of previous approaches. We tested the new analysis techniques by comparing the xylem network of two populations of the herbaceous species Verbascum thapsus collected at a dry and moist site on Big Island (Hawaii, USA). ROXAS accurately, objectively and reproducibly detected grouped and solitary vessels in high-resolution images of entire root cross sections, and calculated different and partly novel vessel grouping parameters, e.g. the percentage of grouped (vs. solitary) vessels among different vessel size classes. Individuals at the dry site showed a higher degree of vessel grouping, less solitary vessels, greater maximum vessel sizes and an increase of the percentage of grouped vessels with increasing vessel size. The potential, but also some limitations of automated image analysis and the proposed novel parameters are discussed.

Measurements of seed coat fragments in cotton fibers and fabrics

2011 ◽  
Vol 81 (19) ◽  
pp. 1983-1994 ◽  
Author(s):  
Patricia Damian Bel ◽  
Bugao Xu
Keyword(s):  
Image Analysis ◽  
Seed Coat ◽  
Automated Image Analysis ◽  
Analysis Tool ◽  
Image Analysis System ◽  
Cotton Industry ◽  
Immature Seeds ◽  
Analysis System ◽  
Financial Losses ◽  
Hand Sorting

Seed coat fragments (SCFs) are the parts of a seed coat that have been broken from the surface of either mature or immature seeds during mechanical processing. SCFs can cause spinning problems and fabric defects, which ultimately cause financial losses to the cotton industry. The objective of this study was to develop and evaluate an image-analysis tool that detects SCFs on fabrics and compares various methods of detection of SCFs in fiber and fabric. The first part of this paper looks at 12 international cottons (a broad range of cottons from distinctly different regions). The version called AFISPro is used in these studies. The SCFs in these fibers were measured by hand sorting, the Shirley Analyzer and the Advanced Fiber Information System (AFIS). The SCFs in the fabrics (made from the same cottons) were measured by hand counting and an automated image-analysis system (Autorate). The Autorate SCF fabric data had a high correlation with the hand-counting SCF fabric data. The same 12 international cotton samples and an additional 12 international cottons were used for the AFISPro studies, since AFISPro is much faster than hand sorting. Comparison of the fiber and fabric data showed a promising relationship between the AFIS SCF measurement and the SCF fabric data.

Automated Image Analysis Of Nuclear And Cytoplasmic Changes In Exfoliated Cells From Tracheas Treated With Carcinogen

1977 ◽  
Vol 35 ◽  
pp. 220-221
Author(s):  
S.F. Stinson ◽  
J.C. Lilga ◽  
M.B. Sporn
Keyword(s):  
Image Analysis ◽  
Pattern Analysis ◽  
Relative Proportion ◽  
Automated Image Analysis ◽  
Image Analyzer ◽  
Cross Sectional ◽  
Exfoliated Cells ◽  
Neoplastic Lesions ◽  
Analysis System ◽  
Morphologic Criterion

Increased nuclear size, resulting in an increase in the relative proportion of nuclear to cytoplasmic sizes, is an important morphologic criterion for the evaluation of neoplastic and pre-neoplastic cells. This paper describes investigations into the suitability of automated image analysis for quantitating changes in nuclear and cytoplasmic cross-sectional areas in exfoliated cells from tracheas treated with carcinogen.Neoplastic and pre-neoplastic lesions were induced in the tracheas of Syrian hamsters with the carcinogen N-methyl-N-nitrosourea. Cytology samples were collected intra-tracheally with a specially designed catheter (1) and stained by a modified Papanicolaou technique. Three cytology specimens were selected from animals with normal tracheas, 3 from animals with dysplastic changes, and 3 from animals with epidermoid carcinoma. One hundred randomly selected cells on each slide were analyzed with a Bausch and Lomb Pattern Analysis System automated image analyzer.

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