## 3 Results  
In this work, an automatic, reliable method for the quantification of the results of scratch wound healing assays is presented. Our AIM software relies on the computation of local entropy (Equation (1)), thus on the evaluation of the information encoded within the neighborhood of each pixel, to enhance the difference between the cell-free region and the areas containing the cells. Indeed, the wound is characterized by a higher uniformity of color and texture and, thus, by a lower information content that makes it clearly distinguishable through an automatic thresholding procedure. To evaluate the quality of this method and validate its results, a set of scratch wound healing assays was performed. These experiments studied the change in invasiveness, caused by TGF-61, a potent in vitro inducer of EMT, which is thus expected to accelerate the wound healing process, by increasing cell migration and proliferation.  
The images acquired at different time points during these assays were analyzed with three alternative methods beside AIM, and the true wound area was determined for 40% of the images through a manual tracing of its edges by an expert user.  
Figure 1 shows the segmentation, obtained with every considered method, of two representative images acquired at 0 and 48 h post scratch. While at the beginning of the experiment (Figure 1a), the results are equivalent and coherent with the ground truth (reported in yellow in Figure 1), at the end of the experiment (Figure 1b), there is a significant variability, with the wound area obtained with ImageJ being notably larger than the ground truth. This is caused by the loss of regularity of the cell front that leads to the generation of a large number of false positives in the analysis with this method.  
The use of a regular polygon to approximate the wound is associated with a decrease in accuracy, which however does not impact significantly on the wound measure, as empty regions outside the rectangle seem to be compensated by patches of cells within the wound.  
Both TScratch and AIM are associated with a significant improvement in accuracy and the ability of correctly recognizing the wound, even when it has been divided into a number of regions due to the conjunction of wound boundaries during cell migration. This allows one to extend the time course  
Figure 1: Schematization of the analysis here presented. The segmentation, with all the considered methods, of two representative images, acquired at T = 0 (**a**) and T = 48 h (**b**), is reported together with the true wound profile (in yellow). Cyan, green, blue and red represent the segmentations with, respectively, the manual method, imagej, TScratch and AIM (Automatic Invasiveness Measure).  
beyond the point at which traditional scratch wound healing assay analysis methods lose reliability. The result obtained with AIM, however, seems to slightly underestimate the region of interest. This is due to the fact that the computation of local entropy is carried out on a square of a side of 19 pixels centered on the one of interest. This leads to an increase of this parameter at the edges of the wound and to a slight loss of precision of the thresholding. The relevance of this aspect is nevertheless low, because the size of the neighborhood was maintained fixed, and thus, it can be considered as an offset that has no effect in the comparison between different conditions.