scholarly journals Plasticity of Arabidopsis Root Gravitropism throughout a Multidimensional Condition Space Quantified by Automated Image Analysis

2009 ◽  
Vol 152 (1) ◽  
pp. 206-216 ◽  
Author(s):  
Tessa L. Durham Brooks ◽  
Nathan D. Miller ◽  
Edgar P. Spalding
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Arabidopsis Root ◽  
Root Gravitropism

Automated Image Analysis Of Nuclear And Cytoplasmic Changes In Exfoliated Cells From Tracheas Treated With Carcinogen

1977 ◽  
Vol 35 ◽  
pp. 220-221
Author(s):  
S.F. Stinson ◽  
J.C. Lilga ◽  
M.B. Sporn
Keyword(s):  
Image Analysis ◽  
Pattern Analysis ◽  
Relative Proportion ◽  
Automated Image Analysis ◽  
Image Analyzer ◽  
Cross Sectional ◽  
Exfoliated Cells ◽  
Neoplastic Lesions ◽  
Analysis System ◽  
Morphologic Criterion

Increased nuclear size, resulting in an increase in the relative proportion of nuclear to cytoplasmic sizes, is an important morphologic criterion for the evaluation of neoplastic and pre-neoplastic cells. This paper describes investigations into the suitability of automated image analysis for quantitating changes in nuclear and cytoplasmic cross-sectional areas in exfoliated cells from tracheas treated with carcinogen.Neoplastic and pre-neoplastic lesions were induced in the tracheas of Syrian hamsters with the carcinogen N-methyl-N-nitrosourea. Cytology samples were collected intra-tracheally with a specially designed catheter (1) and stained by a modified Papanicolaou technique. Three cytology specimens were selected from animals with normal tracheas, 3 from animals with dysplastic changes, and 3 from animals with epidermoid carcinoma. One hundred randomly selected cells on each slide were analyzed with a Bausch and Lomb Pattern Analysis System automated image analyzer.

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

Interfacing of a TEM/STEM System to a Computer

1981 ◽  
Vol 39 ◽  
pp. 250-251
Author(s):  
P. Hagemann
Keyword(s):  
Image Analysis ◽  
Transmission Rate ◽  
Analytical Electron Microscopy ◽  
Signal Beam ◽  
Automated Image Analysis ◽  
Beam Deflection ◽  
External Control ◽  
Computer Input ◽  
Instrument Control ◽  
Data Acquisition And Processing

The use of computers in the analytical electron microscopy today shows three different trends (1) automated image analysis with dedicated computer systems, (2) instrument control by microprocessors and (3) data acquisition and processing e.g. X-ray or EEL Spectroscopy.While image analysis in the T.E.M. usually needs a television chain to get a sequential transmission suitable as computer input, the STEM system already has this necessary facility. For the EM400T-STEM system therefore an interface was developed, that allows external control of the beam deflection in TEM as well as the control of the STEM probe and video signal/beam brightness on the STEM screen.The interface sends and receives analogue signals so that the transmission rate is determined by the convertors in the actual computer periphery.

scholarly journals Author Correction: Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Julian Bär ◽  
Mathilde Boumasmoud ◽  
Roger D. Kouyos ◽  
Annelies S. Zinkernagel ◽  
Clément Vulin
Keyword(s):  
Image Analysis ◽  
Growth Dynamics ◽  
Colony Growth ◽  
Automated Image Analysis ◽  
Analysis Application

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Scoring of radiation-induced microuclei in cytokinesis-blocked human lymphocytes by automated image analysis

Cytometry ◽  
1994 ◽  
Vol 17 (2) ◽  
pp. 119-127 ◽  
Author(s):  
F. Verhaegen ◽  
A. Vral ◽  
J. Seuntjens ◽  
N. W. Schipper ◽  
L. de Ridder ◽  
...  
Keyword(s):  
Image Analysis ◽  
Human Lymphocytes ◽  
Automated Image Analysis ◽  
Radiation Induced

An automated image analysis platform for the study of weakly -adhered cells

Biofouling ◽  
2021 ◽  
pp. 1-10
Author(s):  
Zhijing Wan ◽  
Ben T. MacVicar ◽  
Shea Wyatt ◽  
Diana E. Varela ◽  
Rajkumar Padmawar ◽  
...  
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Platform

scholarly journals Yeast Morphology Assessment through Automated Image Analysis during Fermentation

Fermentation ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 44
Author(s):  
Mario Guadalupe-Daqui ◽  
Mandi Chen ◽  
Katherine A. Thompson-Witrick ◽  
Andrew J. MacIntosh
Keyword(s):  
Image Analysis ◽  
High Stress ◽  
Cross Sectional Area ◽  
Automated Image Analysis ◽  
Yeast Cells ◽  
Morphological Properties ◽  
Cell Area ◽  
Sectional Area ◽  
Cross Sectional ◽  
Industrial Fermentation

The kinetics and success of an industrial fermentation are dependent upon the health of the microorganism(s) responsible. Saccharomyces sp. are the most commonly used organisms in food and beverage production; consequently, many metrics of yeast health and stress have been previously correlated with morphological changes to fermentations kinetics. Many researchers and industries use machine vision to count yeast and assess health through dyes and image analysis. This study assessed known physical differences through automated image analysis taken throughout ongoing high stress fermentations at various temperatures (30 °C and 35 °C). Measured parameters included sugar consumption rate, number of yeast cells in suspension, yeast cross-sectional area, and vacuole cross-sectional area. The cell morphological properties were analyzed automatically using ImageJ software and validated using manual assessment. It was found that there were significant changes in cell area and ratio of vacuole to cell area over the fermentation. These changes were temperature dependent. The changes in morphology have implications for rates of cellular reactions and efficiency within industrial fermentation processes. The use of automated image analysis to quantify these parameters is possible using currently available systems and will provide additional tools to enhance our understanding of the fermentation process.

scholarly journals Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis

Soft Matter ◽  
2021 ◽  
Author(s):  
Muammer Y. Yaman ◽  
Kathryn N. Guye ◽  
Maxim Ziatdinov ◽  
Hao Shen ◽  
David Baker ◽  
...  
Keyword(s):  
Image Analysis ◽  
De Novo ◽  
Automated Image Analysis ◽  
Analysis Tool ◽  
Au Nanorods

In this study, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates using automated image analysis tool.

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 Machine learning-based classification of mitochondrial morphology in primary neurons and brain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Garrett M. Fogo ◽  
Anthony R. Anzell ◽  
Kathleen J. Maheras ◽  
Sarita Raghunayakula ◽  
Joseph M. Wider ◽  
...  
Keyword(s):  
Image Analysis ◽  
Cortical Neurons ◽  
Mitochondrial Dynamics ◽  
Automated Image Analysis ◽  
Mitochondrial Morphology ◽  
Analysis Pipeline ◽  
Genetic Ablation ◽  
Block Face

AbstractThe mitochondrial network continually undergoes events of fission and fusion. Under physiologic conditions, the network is in equilibrium and is characterized by the presence of both elongated and punctate mitochondria. However, this balanced, homeostatic mitochondrial profile can change morphologic distribution in response to various stressors. Therefore, it is imperative to develop a method that robustly measures mitochondrial morphology with high accuracy. Here, we developed a semi-automated image analysis pipeline for the quantitation of mitochondrial morphology for both in vitro and in vivo applications. The image analysis pipeline was generated and validated utilizing images of primary cortical neurons from transgenic mice, allowing genetic ablation of key components of mitochondrial dynamics. This analysis pipeline was further extended to evaluate mitochondrial morphology in vivo through immunolabeling of brain sections as well as serial block-face scanning electron microscopy. These data demonstrate a highly specific and sensitive method that accurately classifies distinct physiological and pathological mitochondrial morphologies. Furthermore, this workflow employs the use of readily available, free open-source software designed for high throughput image processing, segmentation, and analysis that is customizable to various biological models.

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