FIGURE

Fig. 4

ID
ZDB-FIG-171208-13
Publication
Sironi et al., 2014 - In vivo flow mapping in complex vessel networks by single image correlation
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Fig. 4

Measurement of the blood flow speed in the hepatic microcirculation on a wide field of view.

(a) xy-image acquired by detecting the photoluminescence (shown in white) of 5-nm QDs (λexc = 900 nm, detection bandwidth = 640–690 nm); the lower right corner corresponds to the same region analysed in Figure 3. fline = 627 Hz, δx = 0.102 μm, scale bar, 15 μm. CCFs have been derived on the selected ROIs (~ 100 × 50–200 × 100 pixels) for (J-I)δx = 0.51–2.55 μm; the estimated |v| and |v|0, recovered by the fit (equation (3)) and from the peak time (equation (4)) of the experimental CCFs, are reported in Table 1. (b) Schematic of the vessel centrelines for the image in (a). In each ROI, the arrow defines the flow direction and the color codes for the speed value |v|. Vessels not analysed are shown in grey. (c) CCFs computed for (J-I)δx = 2.04 μm in ROIs 5, 6 and 11 (errors are within the size of data points). The fit (equation (3)) led to |v| = 499 ± 18 μm/s in ROI 5, |v| = 187 ± 2 μm/s in ROI 6 and |v| = 396 ± 3 μm/s in ROI 11; as expected, the CCF peak shifts toward shorter lag times as the flow speed increases.

Expression Data

Expression Detail
Antibody Labeling
Phenotype Data

Phenotype Detail
Acknowledgments
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