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Publications

Search Publications by

John T. Elliott (Fed)

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Displaying 26 - 50 of 66

Measurement Uncertainty in Cell Image Segmentation Data Analysis

August 13, 2013
Author(s)
Jin Chu Wu, Michael W. Halter, Raghu N. Kacker, John T. Elliott, Anne L. Plant
Cell image segmentation is a part of quantitative studies regarding cell movement and cell behavior, and it plays a critical role in molecular biology and cellular biochemistry. Therefore, it is fundamentally important to evaluate the performance levels of

NIST Gold Nanoparticle Reference Materials Do Not Induce Oxidative DNA Damage

February 1, 2013
Author(s)
Bryant C. Nelson, Donald H. Atha, John T. Elliott, Bryce J. Marquis, Elijah J. Petersen, Danielle Cleveland, Stephanie S. Watson, I-Hsiang Tseng, Andrew Dillon, Melissa Theodore, Joany Jackman
Well-characterized, nanoparticle reference materials are urgently needed for nanomaterial toxicity studies. The National Institute of Standards and Technology has developed three gold nanoparticle (AuNP) reference materials (10 nm, 30 nm, 60 nm) to address

Quantitative Methods to Characterize Cell Lines: Comparison of Cells from Marine and Terrestrial Mammals.

July 28, 2012
Author(s)
Tighe Spurlin, John T. Elliott, Michael W. Halter, Kiran Bhadriraju, Alessandro Tona, Anne L. Plant, Annalaura Mancia, Bobby L. Middlebrooks, Gregory W. Warr
Descriptive terms are often used to characterize cells in culture, but the use of nonquantitative and poorly defined terms can lead to ambiguities when comparing data from different laboratories. Although recently there has been a good deal of interest in

A New Measure in Cell Image Segmentation Data Analysis

July 24, 2012
Author(s)
Jin Chu Wu, Michael W. Halter, Raghu N. Kacker, John T. Elliott
Cell image segmentation (CIS) is critical for quantitative imaging in cytometric analyses. The data derived after segmentation can be used to infer cellular function. To evaluate CIS algorithms, first for dealing with comparisons of single cells treated as

Evaluation of Segmentation Algorithms on Cell Populations Using CDF Curves

February 24, 2012
Author(s)
Robert C. Hagwood, Javier Bernal, Michael W. Halter, John T. Elliott
Cell segmentation is a critical step in the analysis pipeline for most imaging cytometry experiments and the segmentation algorithm can effect the quantitative data derived from image analysis. Methods to evaluate segmentation algorithms are important for

New Concepts for Building Vocabulary for Cell Image Ontologies

December 21, 2011
Author(s)
Anne L. Plant, John T. Elliott, Talapady N. Bhat
Background: We present an approach to cell image databasing that is compatible with searching across a global federation of independent image databases. The variety of biological experiments and data that practitioners would like to access and share is

Comparison of segmentation algorithms for fluorescence microscopy images of cells

June 14, 2011
Author(s)
Alden A. Dima, John T. Elliott, James J. Filliben, Michael W. Halter, Adele P. Peskin, Javier Bernal, Marcin Kociolek, Mary C. Brady, Hai C. Tang, Anne L. Plant
Segmentation results from nine different segmentation techniques applied to two different cell lines and five different sets of imaging conditions were compared. Significant variability in the results of segmentation was observed that was due solely to

Reproducibility and Robustness of a Real-Time Microfluidic Cell Toxicity Assay

May 15, 2011
Author(s)
Gregory A. Cooksey, John T. Elliott, Anne L. Plant
Numerous opportunities exist to apply microfluidic technology to high-throughput and high-content cell-based assays. However, maximizing the value of these assays for drug discovery, screening or toxicity evaluation, for example, will require validation of

Predicting Segmentation Accuracy for Biological Cell Images

December 15, 2010
Author(s)
Adele P. Peskin, Alden A. Dima, Joe Chalfoun, John T. Elliott
We have performed segmentation procedures on a large number of images from two mammalian cell lines that were seeded at low density, in order to study trends in the segmentation results and make predictions about cellular features that affect segmentation

A Human Inspired Local Ratio-Based Algorithm for Edge Detection in Fluorescent Cell Images

November 25, 2010
Author(s)
Adele P. Peskin, Joe Chalfoun, Alden A. Dima, John T. Elliott, James J. Filliben
We have developed a new semi-automated method for segmenting images of biological cells seeded at low density on tissue culture substrates, which we use to improve the generation of reference data for the evaluation of automated segmentation algorithms

Biological Cell Feature Identification by a Modified Watershed-Merging Algorithm

November 24, 2010
Author(s)
David E. Gilsinn, Kiran Bhadriraju, John T. Elliott
Biological cells are composed of many subsystems and organelles. The subsystem called the cytoskeleton is composed of long rod-shaped structures. They give the cell form and help attach the cell to the substrate and neighbors. One of the filaments is

A mechanistically relevant cytotoxicity assay based on the detection of cellular GFP

August 1, 2009
Author(s)
Michael W. Halter, Jamie L. Almeida, Alessandro Tona, Kenneth D. Cole, Anne L. Plant, John T. Elliott
Cell-based assays for measuring ribosome inhibition by proteins such as the plant toxin ricin are important for characterizing decontamination strategies and developing detection technologies for field use. We report here an assay for ricin that provides a

Cell volume distributions reveal cell growth rates and division times

March 7, 2009
Author(s)
Michael W. Halter, John T. Elliott, Joseph B. Hubbard, Alessandro Tona, Anne L. Plant
A population of cells in culture displays a range of phenotypic responses, even when those cells are derived from a single cell and are exposed to a homogeneous environment. Phenotypic variability can have a number of sources, including the variable rates

The Stiffness of Collagen Fibrils Influences Vascular Smooth Muscle Cell Phenotype

March 1, 2007
Author(s)
Dennis P. McDaniel, Gordon A. Shaw, John T. Elliott, Kiran Bhadriraju, Curtis W. Meuse, Koo-Hyun Chung, Anne L. Plant
Cells receive signals from the extracellular matrix through receptor-dependent interactions, but they are also influenced by the mechanical properties of the matrix. While bulk properties of substrates have been shown to effect cell behavior, we show here