Innovative parameters obtained for digital analysis of microscopic images to evaluate in vitro hemorheological action of anesthetics

2015 ◽  
Author(s):  
Analía I. Alet ◽  
Sabrina Basso ◽  
Marcela Delannoy ◽  
Nicolás A. Alet ◽  
Mabel D'Arrigo ◽  
...  
Keyword(s):  
Digital Analysis ◽  
Microscopic Images

scholarly journals OC_Finder: A deep learning-based software for osteoclast segmentation, counting, and classification

2021 ◽  
Author(s):  
Xiao Wang ◽  
Mizuho Kittaka ◽  
Yilin He ◽  
Yiwei Zhang ◽  
Yasuyoshi Ueki ◽  
...  
Keyword(s):  
Deep Learning ◽  
Bone Matrix ◽  
Osteoclast Formation ◽  
Precursor Cells ◽  
Automated System ◽  
Tartrate Resistant Acid Phosphatase ◽  
Specific Cell ◽  
Microscopic Images ◽  
Multinucleated Cells

Osteoclasts are multinucleated cells that exclusively resorb bone matrix proteins and minerals on the bone surface. They differentiate from monocyte/macrophage-lineage cells in the presence of osteoclastogenic cytokines such as the receptor activator of nuclear factor-κB ligand (RANKL) and are stained positive for tartrate-resistant acid phosphatase (TRAP). In vitro, osteoclast formation assays are commonly used to assess the capacity of osteoclast precursor cells for differentiating into osteoclasts wherein the number of TRAP-positive multinucleated cells are counted as osteoclasts. Osteoclasts are manually identified on cell culture dishes by human eyes, which is a labor-intensive process. Moreover, the manual procedure is not objective and result in lack of reproducibility. To accelerate the process and reduce the workload for counting the number of osteoclasts, we developed OC_Finder, a fully automated system for identifying osteoclasts in microscopic images. OC_Finder consists of segmentation and classification steps. OC_Finder detected osteoclasts differentiated from wild-type and Sh3bp2KI/+ precursor cells at a 99.4% accuracy for segmentation and at a 98.1% accuracy for classification. The number of osteoclasts classified by OC_Finder was at the same accuracy level with manual counting by a human expert. Together, successful development of OC_Finder suggests that deep learning is a useful tool to perform prompt and accurate unbiased classification and detection of specific cell types in microscopic images.

Digital analysis of microscopic images of blood cells for pathological diagnostics

2004 ◽  
Author(s):  
C. Zambrano Velasco ◽  
F. Correa ◽  
L. Pencue Fierro ◽  
M. Patino ◽  
Jaury Leon-Tellez
Keyword(s):  
Blood Cells ◽  
Digital Analysis ◽  
Microscopic Images

Digital Analysis of Microscopic Images in Medicine

2015 ◽  
Vol 10 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Nilanjan Dey ◽  
AmiraS. Ashour ◽  
AhmedS. Ashour ◽  
Aarti Singh
Keyword(s):  
Digital Analysis ◽  
Microscopic Images

scholarly journals The processing of staphylococcal biofilm images from Fluorescence and Confocal Microscopy to assess in vitro efficacy of antiseptic molecules

2021 ◽  
Author(s):  
Adam Feliks Junka ◽  
Grzegorz Krasowski ◽  
Pawel Migdal ◽  
Marta Woroszylo ◽  
Karol Fijalkowski ◽  
...  
Keyword(s):  
Quantitative Methods ◽  
Live Cells ◽  
Parametric Image ◽  
Microscopic Images ◽  
Cellular Density ◽  
Parametric Data ◽  
Method Of Assessment ◽  
Syto 9 ◽  
The Impact

The in vitro efficacy of locally applied antiseptic molecules against staphylococcal biofilm is frequently assessed by a set of standard quantitative and semi-quantitative methods. The development of software for parametric image processing allowed to obtain parametric data also from microscopic images of biofilm dyed with a variety of dyes, especially with propidium iodine and SYTO-9, differentiating dead from live cells. In this work, using confocal/epifluorescent microscopy, we analyzed such major properties of staphylococcal biofilm in vitro as its thickness, cellular density and share of Live/Dead cells within its individual parts. We also scrutinized the impact of sample preparation and antiseptic introduction on the outcome obtained. As a result of our analyses we developed a revelatory method of assessment of the impact of antiseptic agents on staphylococcal biofilm in vitro, in which the microscopic images are processed with the use of ABE formula (Antiseptics Biofilm Eradication) which implements all the data and phenomena detected and revealed within the course of this study. We tested ABE with regard to polyhexanide, povidone-iodine and hypochlorous antiseptics and found a high correlation between this parameter and the results obtained by means of traditional techniques. Taking into account the fact that in vitro results of the efficacy of antiseptic agents against staphylococcal biofilm are frequently applied to back up their use in hospitals and ambulatory units, our work should be considered an important tool providing reliable, parametric data with this regard.

scholarly journals 3D digital analysis of tooth movement with magnets and elastics in vitro

Heliyon ◽  
2021 ◽  
pp. e07507
Author(s):  
Yoshiki Ishida ◽  
Yukinori Kuwajima ◽  
Kaho Ogawa ◽  
Cliff Lee ◽  
John Da Silva ◽  
...  
Keyword(s):  
Tooth Movement ◽  
Digital Analysis

In vitro quantification of changes in human dentine tubule parameters using SEM and digital analysis

2005 ◽  
Vol 32 (8) ◽  
pp. 589-597 ◽  
Author(s):  
T. R. AHMED ◽  
N. J. MORDAN ◽  
M. S. GILTHORPE ◽  
D. G. GILLAM
Keyword(s):  
Digital Analysis ◽  
Human Dentine ◽  
Dentine Tubule
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