Characterization of the structure and the size distribution of branched polymers formed by co-polymerization of MMA and EGDMA

1999 ◽  
Vol 9 (1) ◽  
pp. 83-91 ◽  
Author(s):  
V. Lesturgeon ◽  
D. Durand ◽  
T. Nicolai
Keyword(s):  
Size Distribution ◽  
Branched Polymers

Characterization of Pancreas at Diabetic Patients in CT images using Texture Analysis

2017 ◽  
Vol 7 (7) ◽  
pp. 8
Author(s):  
Mona E. Elbashier ◽  
Suhaib Alameen ◽  
Caroline Edward Ayad ◽  
Mohamed E. M. Gar-Elnabi
Keyword(s):  
Size Distribution ◽  
Texture Analysis ◽  
Classification Accuracy ◽  
Ct Images ◽  
Diabetic Patients ◽  
Gray Level ◽  
Grey Level ◽  
Run Length ◽  
Interactive Data

This study concern to characterize the pancreas areato head, body and tail using Gray Level Run Length Matrix (GLRLM) and extract classification features from CT images. The GLRLM techniques included eleven’s features. To find the gray level distribution in CT images it complements the GLRLM features extracted from CT images with runs of gray level in pixels and estimate the size distribution of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level distribution of images. The results show that the Gray Level Run Length Matrix and  features give classification accuracy of pancreashead 89.2%, body 93.6 and the tail classification accuracy 93.5%. The overall classification accuracy of pancreas area 92.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate pancreas area names.

scholarly journals EVQuant; high-throughput quantification and characterization of extracellular vesicle (sub)populations

2020 ◽  
Author(s):  
T.A. Hartjes ◽  
J.A. Slotman ◽  
M.S. Vredenbregt ◽  
N. Dits ◽  
R. Van der Meel ◽  
...  
Keyword(s):  
Protein Content ◽  
Size Distribution ◽  
High Throughput ◽  
Liquid Biopsy ◽  
Ideal Liquid ◽  
Extracellular Vesicle ◽  
Cell Of Origin ◽  
Clinical Implementation ◽  
High Throughput Assay

AbstractExtracellular vesicles (EVs) reflect the cell of origin in terms of nucleic acids and protein content. They are found in biofluids and represent an ideal liquid biopsy biomarker source for many diseases. Unfortunately, clinical implementation is limited by available technologies for EV analysis. We have developed a simple, robust and sensitive microscopy-based high-throughput assay (EVQuant) to overcome these limitations and allow widespread use in the EV community. The EVQuant assay can detect individual immobilized EVs as small as 35 nm and determine their concentration in biofluids without extensive EV isolation or purification procedures. It can also identify specific EV subpopulations based on combinations of biomarkers and is used here to identify prostate-derived urinary EVs as CD9-/CD63+. Moreover, characterization of individual EVs allows analysis of their size distribution. The ability to identify, quantify and characterize EV (sub-)populations in high-throughput substantially extents the applicability of the EVQuant assay over most current EV quantification assays.

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