John T. Elliott

Learn More
The analysis of fluorescence microscopy of cells often requires the determination of cell edges. This is typically done using segmentation techniques that separate the cell objects in an image from the surrounding background. This study compares segmentation results from nine different segmentation techniques applied to two different cell lines and five(More)
BACKGROUND In anchorage dependent cells, myosin generated contractile forces affect events closely associated with adhesion such as the formation of stress fibers and focal adhesions, and temporally distal events such as entry of the cell into S-phase. As occurs in many signaling pathways, a phosphorylation reaction (in this case, phosphorylation of myosin(More)
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 accuracy. By comparing segmentation results from approximately 40000 cells, we find a linear(More)
BACKGROUND The use of highly reproducible and spatiallyhomogeneous thin film matrices permits automated microscopy and quantitative determination of the response of hundreds of cells in a population. Using thin films of extracellular matrix proteins, we have quantified, on a cell-by-cell basis, phenotypic parameters of cells on different extracellular(More)
BACKGROUND There are significant challenges associated with the building of ontologies for cell biology experiments including the large numbers of terms and their synonyms. These challenges make it difficult to simultaneously query data from multiple experiments or ontologies. If vocabulary terms were consistently used and reused across and within(More)
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. The method was designed to mimic manual cell segmentation and is based on a model of human visual(More)
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 two-dimensional objects, a misclassification error rate (MER) is defined as a weighted sum of the(More)
Insulin and inflammatory cytokines may be involved in equine laminitis, which might be associated with digital vascular dysfunction. This study determined the effects of TNF-α and insulin on the endothelial-dependent relaxant responses of equine digital blood vessels and on equine digital vein endothelial cell (EDVEC) cGMP production. Isolated rings of(More)
We propose a new strategy for estimating the number of cellular objects that should be manually segmented for evaluating the segmentation performance of an algorithm. The strategy uses geometric and edge quality measurements that are directly related to segmentation performance, but do not require highly accurate segmentation. Sample sizes are determined(More)
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 cell image segmentation algorithms. In our previous study, the performance metrics for cell image(More)