scholarly journals New image analysis method for the estimation of global and spatial changes in fruit microstructure

2016 ◽  
Vol 30 (2) ◽  
pp. 219-229 ◽  
Author(s):  
Piotr M. Pieczywek ◽  
Justyna Cybulska ◽  
Barbara Dyki ◽  
Dorota Konopacka ◽  
Monika Mieszczakowska-Frąc ◽  
...  
Keyword(s):  
Cell Wall ◽  
Image Analysis ◽  
Structural Changes ◽  
Sucrose Solution ◽  
Global Analysis ◽  
Cell Wall Fraction ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Tissue Samples ◽  
Microscopy Images

Abstract A new image analysis method for the spatial characterization of microscopy images of fruit microstructure is proposed in order to analyse the heterogeneous microstructure of unprocessed fruit and the possible inhomogeneous effects of various technological treatments on this microstructure. The micro-structure of tissue samples was characterized using the global statistics of size and shape parameters calculated for all visible objects. Global analysis was supported by a novel algorithm that allowed for drawing of the maps of the cell wall fraction from microscopy images and for the analysis of both global and local compaction or loosening of tissue. The spatial distribution of the cell wall fraction was visualised in the convenient form of bivariate histograms. To test the developed image analysis protocols, structural changes resulting from ultrasonic and osmotic treatments of apple tissue samples were studied. Peeled and cored apples were submersed in a liquid medium (distilled water or 60 °Bx sucrose solution) for 45 and 90 min with and without ultrasonic treatment. After these treatment procedures, tissue samples were cut into slices, stained and imaged using a microscope. The proposed method allowed to characterise the effects of different sample treatments.

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

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.

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