Application of Image Analysis Method Combined with Microhardness Measurement to Determine Phase Fractions

2021 ◽  
Vol 1016 ◽  
pp. 1153-1158
Author(s):  
Aarne Pohjonen ◽  
Sami Koskenniska ◽  
Juha Uusitalo ◽  
Tun Tun Nyo ◽  
Jari Larkiola ◽  
...  
Keyword(s):  
Image Analysis ◽  
Isothermal Holding ◽  
Microhardness Measurement ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Microscope Image ◽  
Different Temperatures ◽  
Microscopy Images

We have determined different phase fractions from microscopy images using semi-automated image analysis fitting technique, and in addition we have classified each phase according to its hardness. The distribution of grayscale pixels of different phases is first characterised separately for each phase, which are sampled from the microscope image. After this the distributions of the separate phases are fitted to give the corresponding distribution of the whole image. The microhardness measurement provides reliability on the classification of the different phases to ferrite, bainite or martensite. In addition to describing the applied techniques in detail, we present the results obtained from the analysis for one steel subjected to isothermal holding experiments at different temperatures.

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 Proof of Concept for an Automated Image Analysis Method to Quantify Rat Bone Marrow Hematopoietic Lineages on H&E Sections

2018 ◽  
Vol 46 (3) ◽  
pp. 336-347 ◽  
Author(s):  
Cleopatra Kozlowski ◽  
Aaron Fullerton ◽  
Gary Cain ◽  
Paula Katavolos ◽  
Joseph Bravo ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Image Analysis ◽  
Cell Density ◽  
Bone Marrow Cell ◽  
Marrow Cell ◽  
Automated Image Analysis ◽  
Computer Algorithm ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Rat Bone

The bone marrow is an important site for assessment of the hematopoietic toxicity of new drug candidates. Here, we extended our previous work, where we developed a computer algorithm to automatically quantitate overall bone marrow cell density by analyzing digitized images of standard hematoxylin and eosin (H&E) slides of rat bone marrow and further evaluated the capability to quantify myeloid: erythroid + lymphoid (M:EL) ratio and megakaryocyte cell density. We tested the algorithm in a toxicity study, where rats were dosed with two molecules known to affect bone marrow composition, monomethyl auristatin E, and a Bcl-xL inhibitor. The image analysis method detected significant changes in M:EL and megakaryocyte number that were either not found or semiquantitatively described by manual microscopic observation of the same slides. The image analysis results were consistent with other more established but time-consuming methods that measure changes in bone marrow cell composition: smear cytology, flow cytometry, and microscopic assessment. Our work demonstrates the feasibility of a rapid and more quantitative assessment of changes in bone marrow cell lineage composition using a computer algorithm compared to microscopic examination of H&E-stained bone marrow sections.

scholarly journals Erratum

2018 ◽  
Vol 46 (6) ◽  
pp. 722-722
Keyword(s):  
Bone Marrow ◽  
Image Analysis ◽  
Automated Image Analysis ◽  
Proof Of Concept ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Bone Marrow Cellularity ◽  
Marrow Cellularity ◽  
Rat Bone

Kozlowski, C., Brumm, J., and Cain, G. (2018). An Automated Image Analysis Method to Quantify Veterinary Bone Marrow Cellularity on H&E Sections. Tox Path46, 324–335. (Original DOI: 10.1177/0192623318766457). Kozlowski, C., Fullerton, A., Cain, G., Katavolos, P., Bravo, J., and Tarrant, J. M. (2018). Proof of Concept for an Automated Image Analysis Method to Quantify Rat Bone Marrow Hematopoietic Lineages on H&E Sections. Tox Path46, 336–347. (Oringinal DOI: 10.1177/0192623318766458). In the print issue and initial version of the online issue, the figures for Kozlowski, Brumm, and Cain were mistakenly placed into Kozlowski, Fullerton, et al., and vice versa. The online versions of both articles have been updated to display the appropriate figures.

scholarly journals An Automated Image Analysis Method for Segmenting Fluorescent Bacteria in Three Dimensions

Biochemistry ◽  
2017 ◽  
Vol 57 (2) ◽  
pp. 209-215 ◽  
Author(s):  
Matthew A. Reyer ◽  
Eric L. McLean ◽  
Shriram Chennakesavalu ◽  
Jingyi Fei
Keyword(s):  
Image Analysis ◽  
Three Dimensions ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method

scholarly journals Automated image analysis of a glomerular injury marker desmin in spontaneously diabetic Torii rats treated with losartan

2014 ◽  
Vol 222 (1) ◽  
pp. 43-51 ◽  
Author(s):  
Tetsuhiro Kakimoto ◽  
Kinya Okada ◽  
Yoshihiro Hirohashi ◽  
Raissa Relator ◽  
Mizue Kawai ◽  
...  
Keyword(s):  
Image Analysis ◽  
Diabetic Nephropathy ◽  
Early Stage ◽  
Automated Image Analysis ◽  
Angiotensin Ii Receptor Blocker ◽  
Analysis Method ◽  
Glomerular Injury ◽  
Image Analysis Method ◽  
Podocyte Injury

Diabetic nephropathy is a major complication in diabetes and a leading cause of end-stage renal failure. Glomerular podocytes are functionally and structurally injured early in diabetic nephropathy. A non-obese type 2 diabetes model, the spontaneously diabetic Torii (SDT) rat, is of increasing preclinical interest because of its pathophysiological similarities to human type 2 diabetic complications including diabetic nephropathy. However, podocyte injury in SDT rat glomeruli and the effect of angiotensin II receptor blocker treatment in the early stage have not been reported in detail. Therefore, we have evaluated early stages of glomerular podocyte damage and the beneficial effect of early treatment with losartan in SDT rats using desmin as a sensitive podocyte injury marker. Moreover, we have developed an automated, computational glomerulus recognition method and illustrated its specific application for quantitatively studying glomerular desmin immunoreactivity. This state-of-the-art method enabled automatic recognition and quantification of glomerular desmin-positive areas, eliminating the need to laboriously trace glomerulus borders by hand. The image analysis method not only enabled assessment of a large number of glomeruli, but also clearly demonstrated that glomerular injury was more severe in the juxtamedullary region than in the superficial cortex region. This applied not only in SDT rat diabetic nephropathy but also in puromycin aminonucleoside-induced nephropathy, which was also studied. The proposed glomerulus image analysis method combined with desmin immunohistochemistry should facilitate evaluations in preclinical drug efficacy studies as well as elucidation of the pathophysiology of diabetic nephropathy.

scholarly journals Automated image-analysis method for the quantification of fiber morphometry and fiber type population in human skeletal muscle

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Perla C. Reyes-Fernandez ◽  
Baptiste Periou ◽  
Xavier Decrouy ◽  
Fréderic Relaix ◽  
François Jérôme Authier
Keyword(s):  
Skeletal Muscle ◽  
Image Analysis ◽  
Human Skeletal Muscle ◽  
Fiber Type ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Type Population
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