A New Algorithm For Cell Tracking Technique

Aly, Ashraf A.; Deris, Safaai; Zaki, Nazar

doi:10.5121/acij.2011.2602

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…Measurements of functional microcirculatory geometry and velocity distributions using image techniques have been made, such as capillaroscopy, orthogonal polarized spectral and a side-stream dark field image [ 63 ]. Ashraf et al [ 65 ] said that “cell mobility analysis is an essential process in many biology studies”, so they have focused in developing a novel algorithm to image segmentation and tracking system conjugating the advantages of topological alignments and snakes, transforming the output of the topological alignments into the input of the active contour model to begin the analysis in the cells’ boundaries and to determine cell mobility [ 65 ]. Pan et al [ 66 ] proposed a bacterial foraging-based edge detection (BFED) algorithm for cell image segmentation.…”

Section: An Overview Of Image Analysis Methods For Microfluidic Blmentioning

confidence: 99%

Manual and Automatic Image Analysis Segmentation Methods for Blood Flow Studies in Microchannels

et al. 2021

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In blood flow studies, image analysis plays an extremely important role to examine raw data obtained by high-speed video microscopy systems. This work shows different ways to process the images which contain various blood phenomena happening in microfluidic devices and in microcirculation. For this purpose, the current methods used for tracking red blood cells (RBCs) flowing through a glass capillary and techniques to measure the cell-free layer thickness in different kinds of microchannels will be presented. Most of the past blood flow experimental data have been collected and analyzed by means of manual methods, that can be extremely reliable, but they are highly time-consuming, user-intensive, repetitive, and the results can be subjective to user-induced errors. For this reason, it is crucial to develop image analysis methods able to obtain the data automatically. Concerning automatic image analysis methods for individual RBCs tracking and to measure the well known microfluidic phenomena cell-free layer, two developed methods are presented and discussed in order to demonstrate their feasibility to obtain accurate data acquisition in such studies. Additionally, a comparison analysis between manual and automatic methods was performed.

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Section: An Overview Of Image Analysis Methods For Microfluidic Blmentioning

confidence: 99%

Manual and Automatic Image Analysis Segmentation Methods for Blood Flow Studies in Microchannels

et al. 2021

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“…Apart from all the cancer diagnostics biomarkers discussed in this work, cells' alterations related to diseases occur in most blood pathologies associated with mechanical and rheological changes. The detection and quantification of mechanical alterations have hundreds of applications in diverse fields, ranging from the analysis of cell biomechanics to the classification of tissue biopsies [64][65][66]. For example, mechanical differences in exosomes and microvesicles reflect changes in cell biomechanics and the cell type, state, treatment, and phenotype [66].…”

Section: Future Trendsmentioning

confidence: 99%