2017 IEEE International Conference on Image Processing (ICIP) 2017
DOI: 10.1109/icip.2017.8296893
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Stromule branch tip detection based on accurate cell image segmentation

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Cited by 2 publications
(4 citation statements)
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“…Data represented as the mean standard error of the mean (SEM), ****p<0.0001 by a Student’s t-test with Welch’s correction. ( E ) A stromule tip was tracked using a combination of fuzzy c-means and active contour algorithm, with shape analysis to calculate the length of the stromule, the tip velocity and the association with microtubules ( Lu et al, 2017 ). Tip associations (green dots) with MTs (gray scale) were mapped over a time series.…”
Section: Resultsmentioning
confidence: 99%
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“…Data represented as the mean standard error of the mean (SEM), ****p<0.0001 by a Student’s t-test with Welch’s correction. ( E ) A stromule tip was tracked using a combination of fuzzy c-means and active contour algorithm, with shape analysis to calculate the length of the stromule, the tip velocity and the association with microtubules ( Lu et al, 2017 ). Tip associations (green dots) with MTs (gray scale) were mapped over a time series.…”
Section: Resultsmentioning
confidence: 99%
“…The velocity of stromule extension was significantly lower when MTs were marked with EB1-Citrine (0.0565 µm/s) compared to GFP-TUA6 (0.146 µm/s) ( Figure 1D ). An automated algorithm for detecting stromule tips in maximum intensity projections was developed ( Lu et al, 2017 ). The MTs were segmented and skeletonized (data not shown).…”
Section: Resultsmentioning
confidence: 99%
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