Development of an SEM image analysis method to characterize intumescent fire retardant char layer

2020 ◽  
Vol 139 ◽  
pp. 105461
Author(s):  
Xiaochun Hu ◽  
Xiaojun Zhu ◽  
Zhiqiang Sun
Keyword(s):  
Image Analysis ◽  
Fire Retardant ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Sem Image ◽  
Char Layer ◽  
Sem Image Analysis

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

A Computerized Image Analysis Method for Measuring Elastic Tissue.

1989 ◽  
Vol 93 (3) ◽  
pp. 358-362 ◽  
Author(s):  
Thomas J. Flotte ◽  
Johanna M. Seddon ◽  
Yuqing Zhang ◽  
Robert J. Glynn ◽  
Kathleen M. Egan ◽  
...  
Keyword(s):  
Image Analysis ◽  
Elastic Tissue ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Computerized Image Analysis

ASSESSMENT OF OSTEOARTHRITIS INITIATIVE–KELLGREN AND LAWRENCE SCORING PROJECTS QUALITY USING COMPUTER ANALYSIS

2010 ◽  
Vol 13 (04) ◽  
pp. 197-201 ◽  
Author(s):  
Lior Shamir ◽  
David T. Felson ◽  
Luigi Ferrucci ◽  
Ilya G. Goldberg
Keyword(s):  
Image Analysis ◽  
Gold Standard ◽  
Population Studies ◽  
Detection Accuracy ◽  
X Rays ◽  
Analysis Method ◽  
Image Analysis Method ◽  
X Ray ◽  
Osteoarthritis Initiative ◽  
Kellgren And Lawrence

The detection of knee osteoarthritis (OA) is a subjective task, and even two highly experienced and well-trained readers might not always agree on a specific case. This problem is noticeable in OA population studies, in which different scoring projects provide significantly different scores for the same knee X-rays. Here we propose a method for quantitative assessment and comparison of knee X-ray scoring projects in OA population studies. The method works by applying an image analysis method that automatically detects OA in knee X-ray images, and comparing the consistency of the scores when using each of the scoring projects as "gold standard." The method was applied to compare the osteoarthritis initiative (OAI) clinic reading derived Kellgren and Lawrence (K&L) scores to central reading, and showed that when using the derived K&L scores the automatic image analysis method was able to accurately differentiate between healthy joints and moderate OA joints in ~70% of the cases. When the OAI central reading scores were used as gold standard, the detection accuracy was elevated to ~77%. These results show that the OAI central readings scores are more consistent with the X-rays, indicating that the central reading better reflects the radiographic features associated with OA, compared to the OAI K&L scores derived from clinic readings.

scholarly journals Recycled Mortars with Ceramic Aggregates. Pore Network Transmutation and Its Relationship with Physical and Mechanical Properties

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1543
Author(s):  
Francisca Guadalupe Cabrera-Covarrubias ◽  
José Manuel Gómez-Soberón ◽  
Carlos Antonio Rosas-Casarez ◽  
Jorge Luis Almaral-Sánchez ◽  
Jesús Manuel Bernal-Camacho
Keyword(s):  
Mechanical Properties ◽  
Image Analysis ◽  
Open Porosity ◽  
Gas Adsorption ◽  
Physical And Mechanical Properties ◽  
Recycled Aggregate ◽  
Bet Surface Area ◽  
Sem Image ◽  
The Relationship ◽  
Sem Image Analysis

The porosity of mortars with recycled ceramic aggregates (10, 20, 30, 50, and 100% as a replacement of natural aggregate) was evaluated and analyzed using three different techniques. The results of gas adsorption (N2), Scanning Electron Microscopy (SEM) image analysis and open porosity allowed establishing the relationship between the recycled aggregate content and the porosity of these mortars, as well as the relationship between porosity and the physical and mechanical properties of the mortars: absorption, density, compressive strength, modulus of elasticity, and drying shrinkage. Using the R2 coefficient and the equation typology as criteria, additional data such as Brunauer, Emmett, and Teller (BET) surface area (N2 adsorption) established significant correlations with the mentioned properties; with SEM image analysis, no explanatory relationships could be established; and with open porosity, revealing relationships were established (R2 > 0.9). With the three techniques, it was confirmed that the increase in porosity is related to the increase in the amount of ceramic aggregate; in particular with gas adsorption (N2) and open porosity. It was concluded that the open porosity technique can explain the behavior of these recycled mortars with more reliable data, in a simple and direct way, linked to its establishment with a more representative sample of the mortar matrix.

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