scholarly journals EpiGraph: an open-source platform to quantify epithelial organization

2017 ◽  
Author(s):  
Pablo Vicente-Munuera ◽  
Pedro Gómez-Gálvez ◽  
Robert J. Tetley ◽  
Cristina Forja ◽  
Antonio Tagua ◽  
...  
Keyword(s):  
Image Analysis ◽  
Open Access ◽  
Analysis Tool ◽  
Distribution Analysis ◽  
Form Complex ◽  
Programming Skills ◽  
User Friendly ◽  
Degree Of Order ◽  
Different Tissues

SUMMARYDuring development, cells must coordinate their differentiation with their growth and organization to form complex multicellular structures such as tissues and organs. Healthy tissues must maintain these structures during homeostasis. Epithelia are packed ensembles of cells from which the different tissues of the organism will originate during embryogenesis. A large barrier to the analysis of the morphogenetic changes in epithelia is the lack of simple tools that enable the quantification of cell arrangements. Here we present EpiGraph, an image analysis tool that quantifies epithelial organization. Our method combines computational geometry and graph theory to measure the degree of order of any packed tissue. EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia. EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected. Importantly, it has been implemented in the open-access platform FIJI. This makes EpiGraph very user friendly, with no programming skills required.

scholarly journals EpiGraph: an open-source platform to quantify epithelial organization

2019 ◽  
Author(s):  
Pablo Vicente-Munuera ◽  
Pedro Gómez-Gálvez ◽  
Robert J Tetley ◽  
Cristina Forja ◽  
Antonio Tagua ◽  
...  
Keyword(s):  
Image Analysis ◽  
Open Access ◽  
Supplementary Information ◽  
Analysis Tool ◽  
Distribution Analysis ◽  
Supplementary Data ◽  
Programming Skills ◽  
User Friendly ◽  
Degree Of Order

Abstract Summary Here we present EpiGraph, an image analysis tool that quantifies epithelial organization. Our method combines computational geometry and graph theory to measure the degree of order of any packed tissue. EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia. EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected. Importantly, it has been implemented in the open-access platform Fiji. This makes EpiGraph very user friendly, with no programming skills required. Availability and implementation EpiGraph is available at https://imagej.net/EpiGraph and the code is accessible (https://github.com/ComplexOrganizationOfLivingMatter/Epigraph) under GPLv3 license. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The Development of a Skin Image Analysis Tool by Using Machine Learning Algorithms

Cosmetics ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 67
Author(s):  
Perry Xiao ◽  
Xu Zhang ◽  
Wei Pan ◽  
Xiang Ou ◽  
Christos Bontozoglou ◽  
...  
Keyword(s):  
Machine Learning ◽  
Image Analysis ◽  
Imaging Techniques ◽  
Learning Algorithms ◽  
Research Work ◽  
Software Tool ◽  
Machine Learning Algorithms ◽  
Analysis Tool ◽  
Skin Imaging ◽  
User Friendly

We present our latest research work on the development of a skin image analysis tool by using machine-learning algorithms. Skin imaging is very import in skin research. Over the years, we have used and developed different types of skin imaging techniques. As the number of skin images and the type of skin images increase, there is a need of a dedicated skin image analysis tool. In this paper, we report the development of such software tool by using the latest MATLAB App Designer. It is simple, user friendly and yet powerful. We intend to make it available on GitHub, so that others can benefit from the software. This is an ongoing project; we are reporting here what we have achieved so far, and more functions will be added to the software in the future.

scholarly journals The Encyclopedia of Proteome Dynamics: the KinoViewer

2018 ◽  
Vol 35 (8) ◽  
pp. 1441-1442 ◽  
Author(s):  
Alejandro Brenes ◽  
Angus I Lamond
Keyword(s):  
Open Access ◽  
Supplementary Information ◽  
Analysis Tool ◽  
Graphical Display ◽  
Visualization Tool ◽  
Dynamic Visualization ◽  
Graphical Interface ◽  
Mouse Cells ◽  
Interactive Data ◽  
User Friendly

Abstract Summary The Encyclopedia of Proteome Dynamics (EPD) ‘KinoViewer’ is an interactive data visualization tool designed for analysis and exploration of both protein and transcript data, showing expression of kinase genes in either human or mouse cells and tissues. The KinoViewer provides a comprehensive, updated graphical display of all human/mouse kinases and an open access analysis tool for the community with a user-friendly graphical interface. Availability and implementation The KinoViewer is based on a manually drawn SVG, which is utilized with D3.js to create a dynamic visualization. It can be accessed at: https://peptracker.com/epd/analytics/. The KinoViewer is currently only accessible through the EPD, it is open access and can be used either to view internal datasets, or used to upload and visualize external user datasets. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals NeuroPM toolbox: integrating Molecular, Neuroimaging and Clinical data for Characterizing Neuropathological Progression and Individual Therapeutic Needs

2020 ◽  
Author(s):  
Yasser Iturria-Medina ◽  
Felix Carbonell ◽  
Atoussa Assadi ◽  
Quadri Adewale ◽  
Ahmed F. Khan ◽  
...  
Keyword(s):  
Open Access ◽  
High Performance ◽  
Large Scale ◽  
Synergistic Interactions ◽  
Academic Researchers ◽  
Cross Platform ◽  
Therapeutic Needs ◽  
User Friendly ◽  
Performance Computing

There is a critical need for a better multiscale and multifactorial understanding of neurological disorders, covering from genes to neuroimaging to clinical factors and treatments effects. Here we present NeuroPM-box, a cross-platform, user-friendly and open-access software for characterizing multiscale and multifactorial brain pathological mechanisms and identifying individual therapeutic needs. The implemented methods have been extensively tested and validated in the neurodegenerative context, but there is not restriction in the kind of disorders that can be analyzed. By using advanced analytic modeling of molecular, neuroimaging and/or cognitive/behavioral data, this framework allows multiple applications, including characterization of: (i) the series of sequential states (e.g. transcriptomic, imaging or clinical alterations) covering decades of disease progression, (ii) intra-brain spreading of pathological factors (e.g. amyloid and tau misfolded proteins), (iii) synergistic interactions between multiple brain biological factors (e.g. direct tau effects on vascular and structural properties), and (iv) biologically-defined patients stratification based on therapeutic needs (i.e. optimum treatments for each patient). All models outputs are biologically interpretable. A 4D-viewer allows visualization of spatiotemporal brain (dis)organization. Originally implemented in MATLAB, NeuroPM-box is compiled as standalone application for Windows, Linux and Mac environments: neuropm-lab.com/software. In a regular workstation, it can analyze over 150 subjects per day, reducing the need for using clusters or High-Performance Computing (HPC) for large-scale datasets. This open-access tool for academic researchers may significantly contribute to a better understanding of complex brain processes and to accelerating the implementation of Precision Medicine (PM) in neurology.

scholarly journals RootAnalyzer: A Cross-Section Image Analysis Tool for Automated Characterization of Root Cells and Tissues

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0137655 ◽  
Author(s):  
Joshua Chopin ◽  
Hamid Laga ◽  
Chun Yuan Huang ◽  
Sigrid Heuer ◽  
Stanley J. Miklavcic
Keyword(s):  
Image Analysis ◽  
Cross Section ◽  
Analysis Tool ◽  
Root Cells

Characterization of Platelet Adhesion under Flow using Microscopic Image Sequence Analysis

2005 ◽  
Vol 28 (7) ◽  
pp. 678-685 ◽  
Author(s):  
M. Machin ◽  
A. Santomaso ◽  
M.R. Cozzi ◽  
M. Battiston ◽  
M. Mazzucato ◽  
...  
Keyword(s):  
Image Analysis ◽  
Blood Platelets ◽  
Lower Surface ◽  
Video Camera ◽  
Flow Chamber ◽  
Artificial Organs ◽  
Analysis Tool ◽  
Glass Coverslip ◽  
Platelet Surface

A method for quantitative analysis of platelet deposition under flow is discussed here. The model system is based upon perfusion of blood platelets over an adhesive substrate immobilized on a glass coverslip acting as the lower surface of a rectangular flow chamber. The perfusion apparatus is mounted onto an inverted microscope equipped with epifluorescent illumination and intensified CCD video camera. Characterization is based on information obtained from a specific image analysis method applied to continuous sequences of microscopical images. Platelet recognition across the sequence of images is based on a time-dependent, bidimensional, gaussian-like pdf. Once a platelet is located, the variation of its position and shape as a function of time (i.e., the platelet history) can be determined. Analyzing the history we can establish if the platelet is moving on the surface, the frequency of this movement and the distance traveled before its resumes the velocity of a non-interacting cell. Therefore, we can determine how long the adhesion would last which is correlated to the resistance of the platelet-substrate bond. This algorithm enables the dynamic quantification of trajectories, as well as residence times, arrest and release frequencies for a high numbers of platelets at the same time. Statistically significant conclusions on platelet-surface interactions can then be obtained. An image analysis tool of this kind can dramatically help the investigation and characterization of the thrombogenic properties of artificial surfaces such as those used in artificial organs and biomedical devices.

A New System For Optomanual Semiautomatic Quantitative Image Analysis

1977 ◽  
Vol 35 ◽  
pp. 210-211
Author(s):  
H.P. Rohr
Keyword(s):  
Image Analysis ◽  
Volume Density ◽  
List Type ◽  
Distribution Analysis ◽  
Type Number ◽  
Point Counting ◽  
Human Eye ◽  
Quantitative Image ◽  
Point Density ◽  
Electronic Counting

Today, in image analysis the broadest possible rationalization and economization have become desirable. Basically, there are two approaches for image analysis: The image analysis through the so-called scanning methods which are usually performed without the human eye and the systems of optical semiautomatic analysis completely relying on the human eye.The new MOP AM 01 opto-manual system (fig.) represents one of the very promising approaches in this field. The instrument consists of an electronic counting and storing unit, which incorporates a microprocessor and a keyboard for choice of measuring parameters, well designed for easy use.Using the MOP AM 01 there are three possibilities of image analysis:the manual point counting,the opto-manual point counting andthe measurement of absolute areas and/or length (size distribution analysis included).To determine a point density for the calculation of the corresponding volume density the intercepts lying within the structure are scanned with the light pen.

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