Following test image segmentation, post processing was applied. First, small instances with pixel area of less than 25% of the image average, were removed. Next, overlapping instances were merged or separated. Where overlapping instances were located, the pixel area of each instance was calculated as was the area of the overlap. Instances sharing more than 50% of their total pixel area, or where 50% of either instance’s pixels overlap, those instances were merged. When the overlapping area comprised less than 10% of one instance, but more than 10% of the other, the overlap was assigned to the instance with the greatest overlap. However, when both instances contributed 10% or less of their pixels to the overlapping region, the entire region was randomly assigned. Lastly, when the overlap comprised less than 50% of each instance, but more than 10%, the overlapping region was split, as shown in Fig. 10.

The first step in dividing an overlap was to find the center of mass of each instance. Next, the two center points were connected by a line segment. The center of the line was then found, and a new line was created, perpendicular to the first and passing through its center point, as well as through the borders of the overlapping regions. The overlapping instances were then split along the second line and each section assigned a different label. Any new small instances created during the split were again removed.

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