Figure 2.

Performance of the filament-tracking routine. (A) We simulated 20 confocal images of a single, fluorescent filament and used the proposed neural network-based tracking routine (○) or a Gaussian deconvolution-based algorithm (■) to track its position. The error on the filament position determination was calculated using Eq. 5. (Inset) A representative intensity profile obtained perpendicular to a microtubule labeled with EGFP-XTP (S/N = 5) in X. laevis melanophores was fitted using the neural network-based tracking routine (continuous line) or a Gaussian function (dotted lines). (B) Twenty confocal images of two intersecting filaments (S/N = 10) were simulated and tracked using the neural network-based tracking routine (○) or a Gaussian deconvolution-based algorithm (■). The confusion regions predicted according to the diffraction limit (▵) and those obtained with the tracking routines are plotted as a function of the intersecting angle.