Ge detection results. This match indicates that varying the threshold value S corresponds to a consistent variation in the spatial distribution of cell density in the spreading cell population. Comparing the edge detection results to the corresponding contours of the cell density, we observe that the Tunicamycin manual edge detection technique MK8931 identifies a range of leading edges corresponding to cell densities of 2?:5 at t 24 hours, 0:9?:2 at t 48 hours and 0:8?:5 at t 72 hours for the barrier assays with 10,000 cells. Equivalent results in Fig. 3E indicates that the manual edge detection technique identifies a range of leading edges corresponding to cell densities of 0:2?:8 , 0:5?:5 and 0:8?:8 , for t 24, 48, 72 hours for the barrier assay with 30,000 cells. In summary, the manual edge detection technique identifies a range of leading edges corresponding to cell densities of approximately 1? of the maximum packing density.Number of Cells 10,Time (hours) 24 48M(t) Manual S High 10.8 25.7 37.8 49.6 65.6 74.M(t) Manual S Low 25.0 50.7 63.5 66.6 82.7 99.M(t) Auto ImageJ 14.4 35.0 49.7 50.8 66.8 68.M(t) Auto Matlab 17.9 34.8 53.8 50.0 71.3 82.30,24 48The cell migration rate in terms of M(t) using equation (1) and the average area results from Table 1. Results are Ronment. CD4+ T cell clones that populate the Th1 effector pool reported for the manual edge detection technique with a high threshold (Manual S high), the manual edge detection technique with a low threshold (Manual S Low), the MATLAB Image Processing Toolbox automatic technique (Auto MATLAB) and the ImageJ automatic technique (Auto ImageJ). doi:10.1371/journal.pone.0067389.tSensitivity of Edge Detection MethodsFigure 3. Physical interpretation of the edge detection results. (A, D): Solutions of equation (2) showing the density profiles near the leading edge at t 0 (dotted black), t 24 (blue), t 48 (red) and t 72 hours (green). Arrows indicate the direction of increasing time. The initial conditions is given by equation (3) with c0 0:22 and c0 0:66 for barrier assays with 10,000 and 30,000 cells, respectively. Numerical solutions of equation (2) are obtained with dr 1:0 mm and dt 0:005 hours, with D 1700 mm2 =hour and D 2900 mm2 =hour for barrier assays with 10,000 and 30,000 cells, respectively. (B,E) The detail of the solutions of equation (2) from the boxed area in (A,D) compared with the scaled manual edge detection results (black) from Figure 2 (A,C). (C,F) Images of a barrier assay with 10,000 and 30,000 cells at t 72 hours, respectively. The contours of the solution of equation (2) are superimposed. The values of the contours are cmin 0:007 and cmax 0:026 for the barrier assay with 10,000 cells, and cmin 0:008 and cmax 0:020 for the barrier assay with 30,000 cells. doi:10.1371/journal.pone.0067389.gThe images in Fig. 3C and Fig. 3F show snapshots from two barrier assays at t 72 hours with 10,000 and 30,000 cells, respectively. To illustrate the location of the leading edge, defined by contoured solutions of equation (2), we superimpose the cmin and cmax contour of the appropriate solution of equation (2). In both cases we observe that the cmin and cmax contours are reasonable approximations to the location of the position of the leading edge of the spreading populations. In each experiment, the difference hPTH (1-34) web between the cmin and cmax contours are relatively large and this recapitulates the sensitivity observed previously in Fig. 1H and Fig. 1I.Discussion and ConclusionsCell migration is an essential aspect of development [1,2], repai.Ge detection results. This match indicates that varying the threshold value S corresponds to a consistent variation in the spatial distribution of cell density in the spreading cell population. Comparing the edge detection results to the corresponding contours of the cell density, we observe that the manual edge detection technique identifies a range of leading edges corresponding to cell densities of 2?:5 at t 24 hours, 0:9?:2 at t 48 hours and 0:8?:5 at t 72 hours for the barrier assays with 10,000 cells. Equivalent results in Fig. 3E indicates that the manual edge detection technique identifies a range of leading edges corresponding to cell densities of 0:2?:8 , 0:5?:5 and 0:8?:8 , for t 24, 48, 72 hours for the barrier assay with 30,000 cells. In summary, the manual edge detection technique identifies a range of leading edges corresponding to cell densities of approximately 1? of the maximum packing density.Number of Cells 10,Time (hours) 24 48M(t) Manual S High 10.8 25.7 37.8 49.6 65.6 74.M(t) Manual S Low 25.0 50.7 63.5 66.6 82.7 99.M(t) Auto ImageJ 14.4 35.0 49.7 50.8 66.8 68.M(t) Auto Matlab 17.9 34.8 53.8 50.0 71.3 82.30,24 48The cell migration rate in terms of M(t) using equation (1) and the average area results from Table 1. Results are reported for the manual edge detection technique with a high threshold (Manual S high), the manual edge detection technique with a low threshold (Manual S Low), the MATLAB Image Processing Toolbox automatic technique (Auto MATLAB) and the ImageJ automatic technique (Auto ImageJ). doi:10.1371/journal.pone.0067389.tSensitivity of Edge Detection MethodsFigure 3. Physical interpretation of the edge detection results. (A, D): Solutions of equation (2) showing the density profiles near the leading edge at t 0 (dotted black), t 24 (blue), t 48 (red) and t 72 hours (green). Arrows indicate the direction of increasing time. The initial conditions is given by equation (3) with c0 0:22 and c0 0:66 for barrier assays with 10,000 and 30,000 cells, respectively. Numerical solutions of equation (2) are obtained with dr 1:0 mm and dt 0:005 hours, with D 1700 mm2 =hour and D 2900 mm2 =hour for barrier assays with 10,000 and 30,000 cells, respectively. (B,E) The detail of the solutions of equation (2) from the boxed area in (A,D) compared with the scaled manual edge detection results (black) from Figure 2 (A,C). (C,F) Images of a barrier assay with 10,000 and 30,000 cells at t 72 hours, respectively. The contours of the solution of equation (2) are superimposed. The values of the contours are cmin 0:007 and cmax 0:026 for the barrier assay with 10,000 cells, and cmin 0:008 and cmax 0:020 for the barrier assay with 30,000 cells. doi:10.1371/journal.pone.0067389.gThe images in Fig. 3C and Fig. 3F show snapshots from two barrier assays at t 72 hours with 10,000 and 30,000 cells, respectively. To illustrate the location of the leading edge, defined by contoured solutions of equation (2), we superimpose the cmin and cmax contour of the appropriate solution of equation (2). In both cases we observe that the cmin and cmax contours are reasonable approximations to the location of the position of the leading edge of the spreading populations. In each experiment, the difference between the cmin and cmax contours are relatively large and this recapitulates the sensitivity observed previously in Fig. 1H and Fig. 1I.Discussion and ConclusionsCell migration is an essential aspect of development [1,2], repai.Ge detection results. This match indicates that varying the threshold value S corresponds to a consistent variation in the spatial distribution of cell density in the spreading cell population. Comparing the edge detection results to the corresponding contours of the cell density, we observe that the manual edge detection technique identifies a range of leading edges corresponding to cell densities of 2?:5 at t 24 hours, 0:9?:2 at t 48 hours and 0:8?:5 at t 72 hours for the barrier assays with 10,000 cells. Equivalent results in Fig. 3E indicates that the manual edge detection technique identifies a range of leading edges corresponding to cell densities of 0:2?:8 , 0:5?:5 and 0:8?:8 , for t 24, 48, 72 hours for the barrier assay with 30,000 cells. In summary, the manual edge detection technique identifies a range of leading edges corresponding to cell densities of approximately 1? of the maximum packing density.Number of Cells 10,Time (hours) 24 48M(t) Manual S High 10.8 25.7 37.8 49.6 65.6 74.M(t) Manual S Low 25.0 50.7 63.5 66.6 82.7 99.M(t) Auto ImageJ 14.4 35.0 49.7 50.8 66.8 68.M(t) Auto Matlab 17.9 34.8 53.8 50.0 71.3 82.30,24 48The cell migration rate in terms of M(t) using equation (1) and the average area results from Table 1. Results are reported for the manual edge detection technique with a high threshold (Manual S high), the manual edge detection technique with a low threshold (Manual S Low), the MATLAB Image Processing Toolbox automatic technique (Auto MATLAB) and the ImageJ automatic technique (Auto ImageJ). doi:10.1371/journal.pone.0067389.tSensitivity of Edge Detection MethodsFigure 3. Physical interpretation of the edge detection results. (A, D): Solutions of equation (2) showing the density profiles near the leading edge at t 0 (dotted black), t 24 (blue), t 48 (red) and t 72 hours (green). Arrows indicate the direction of increasing time. The initial conditions is given by equation (3) with c0 0:22 and c0 0:66 for barrier assays with 10,000 and 30,000 cells, respectively. Numerical solutions of equation (2) are obtained with dr 1:0 mm and dt 0:005 hours, with D 1700 mm2 =hour and D 2900 mm2 =hour for barrier assays with 10,000 and 30,000 cells, respectively. (B,E) The detail of the solutions of equation (2) from the boxed area in (A,D) compared with the scaled manual edge detection results (black) from Figure 2 (A,C). (C,F) Images of a barrier assay with 10,000 and 30,000 cells at t 72 hours, respectively. The contours of the solution of equation (2) are superimposed. The values of the contours are cmin 0:007 and cmax 0:026 for the barrier assay with 10,000 cells, and cmin 0:008 and cmax 0:020 for the barrier assay with 30,000 cells. doi:10.1371/journal.pone.0067389.gThe images in Fig. 3C and Fig. 3F show snapshots from two barrier assays at t 72 hours with 10,000 and 30,000 cells, respectively. To illustrate the location of the leading edge, defined by contoured solutions of equation (2), we superimpose the cmin and cmax contour of the appropriate solution of equation (2). In both cases we observe that the cmin and cmax contours are reasonable approximations to the location of the position of the leading edge of the spreading populations. In each experiment, the difference between the cmin and cmax contours are relatively large and this recapitulates the sensitivity observed previously in Fig. 1H and Fig. 1I.Discussion and ConclusionsCell migration is an essential aspect of development [1,2], repai.Ge detection results. This match indicates that varying the threshold value S corresponds to a consistent variation in the spatial distribution of cell density in the spreading cell population. Comparing the edge detection results to the corresponding contours of the cell density, we observe that the manual edge detection technique identifies a range of leading edges corresponding to cell densities of 2?:5 at t 24 hours, 0:9?:2 at t 48 hours and 0:8?:5 at t 72 hours for the barrier assays with 10,000 cells. Equivalent results in Fig. 3E indicates that the manual edge detection technique identifies a range of leading edges corresponding to cell densities of 0:2?:8 , 0:5?:5 and 0:8?:8 , for t 24, 48, 72 hours for the barrier assay with 30,000 cells. In summary, the manual edge detection technique identifies a range of leading edges corresponding to cell densities of approximately 1? of the maximum packing density.Number of Cells 10,Time (hours) 24 48M(t) Manual S High 10.8 25.7 37.8 49.6 65.6 74.M(t) Manual S Low 25.0 50.7 63.5 66.6 82.7 99.M(t) Auto ImageJ 14.4 35.0 49.7 50.8 66.8 68.M(t) Auto Matlab 17.9 34.8 53.8 50.0 71.3 82.30,24 48The cell migration rate in terms of M(t) using equation (1) and the average area results from Table 1. Results are reported for the manual edge detection technique with a high threshold (Manual S high), the manual edge detection technique with a low threshold (Manual S Low), the MATLAB Image Processing Toolbox automatic technique (Auto MATLAB) and the ImageJ automatic technique (Auto ImageJ). doi:10.1371/journal.pone.0067389.tSensitivity of Edge Detection MethodsFigure 3. Physical interpretation of the edge detection results. (A, D): Solutions of equation (2) showing the density profiles near the leading edge at t 0 (dotted black), t 24 (blue), t 48 (red) and t 72 hours (green). Arrows indicate the direction of increasing time. The initial conditions is given by equation (3) with c0 0:22 and c0 0:66 for barrier assays with 10,000 and 30,000 cells, respectively. Numerical solutions of equation (2) are obtained with dr 1:0 mm and dt 0:005 hours, with D 1700 mm2 =hour and D 2900 mm2 =hour for barrier assays with 10,000 and 30,000 cells, respectively. (B,E) The detail of the solutions of equation (2) from the boxed area in (A,D) compared with the scaled manual edge detection results (black) from Figure 2 (A,C). (C,F) Images of a barrier assay with 10,000 and 30,000 cells at t 72 hours, respectively. The contours of the solution of equation (2) are superimposed. The values of the contours are cmin 0:007 and cmax 0:026 for the barrier assay with 10,000 cells, and cmin 0:008 and cmax 0:020 for the barrier assay with 30,000 cells. doi:10.1371/journal.pone.0067389.gThe images in Fig. 3C and Fig. 3F show snapshots from two barrier assays at t 72 hours with 10,000 and 30,000 cells, respectively. To illustrate the location of the leading edge, defined by contoured solutions of equation (2), we superimpose the cmin and cmax contour of the appropriate solution of equation (2). In both cases we observe that the cmin and cmax contours are reasonable approximations to the location of the position of the leading edge of the spreading populations. In each experiment, the difference between the cmin and cmax contours are relatively large and this recapitulates the sensitivity observed previously in Fig. 1H and Fig. 1I.Discussion and ConclusionsCell migration is an essential aspect of development [1,2], repai.