Sentence examples for image processing cell from inspiring English sources

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The main result in this research is that the HD calculation on a modest sized FPGA is approximately 19 times faster than a state-of-the-art CPU design and 2.5 times faster than the image processing Cell processor.

Given the current state of the art in image processing, cell tracking under noise-free and high-contrast circumstances, such as fluorescently labelled bacteria, is a tractable task.

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In addition to 2D curved surfaces, MorphoGraphX also possesses a rich set of tools for full 3D image processing and cell segmentation, and can be used to easily transfer realistic cell geometries and fluorescent marker data into computational modeling environments.

Tg(hand2 EGFP) pd24 larvae were treated and processed as described (Yin et al., 2012) by imaging on a Zeiss Pascal confocal microscope, and image processing and cell counting were conducted using Fiji (http://fiji.sc/Fiji).sc/Fiji

A wide variety of quantitative biological dynamics data can be directly obtained from experimental measurements by using live-cell imaging and digital image processing; for example, cell division dynamics in Caenorhabditis elegans can be extracted from four-dimensional (4D) microscopic images (Bao et al., 2006; Giurumescu et al., 2012; Kyoda et al., 2013; Sarov et al., 2012).

Cell proliferation was examined by MTT assay, alignment of actin fibers by a designed image processing code, and cell differentiation by fluorescence staining.

This paper describes an efficient image processing method for cell pattern recognition and morphological analysis of images that were affected by uneven background.

Image processing (background substraction, cell segmentation) could be integrated within the same master program.

In fact, cosegmentations promise to be useful in other bioimaging (and eventually image processing) applications beyond cell tracking.

Summary: Automated image processing has allowed cell migration research to evolve to a high-throughput research field.

We have developed a novel approach that combines in vitro live cell labeling, optical microscopy, image processing, high throughput single cell mass spectrometry, and multivariate statistical analysis, to enable cellular classification via multiplexed analysis of cell peptide content.

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