Description of the algorithm.

<p>A. Image of retinal arteriole under no pressure conditions and at 37°C. A_i. Top and bottom walls from the arteriole. The blue lines superimposed are drawn by applying only cost analysis with no edge enhancement. Initial start and end points are used here as part of the cost function detection as shown below in B. A_ii. Inset zoomed from the bottom wall in A_i illustrating adluminal and abluminal edges. B. Left and right panels correspond to images obtained from the vessel in A after convolving with 2 different kernels. Left image shows more pronounced top adluminal and bottom abluminal edges. Right image shows more pronounced top abluminal and bottom adluminal edges. Initial start (s) and end (e) points are also marked in the images. C. Top and bottom walls as in A. The 4 yellow lines superimposed correspond to the detected abluminal and adluminal edges in both walls. D. Estimated mid-wall lines (in yellow) are shown superimposed on the walls of the vessel. E. Binary image used for validation of the middle lines. If the validation fails, parameters are modified (as shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091791#pone-0091791-g002" target="_blank">Fig. 2</a>) and detection is restarted. F. Modified binary image used to adjust the middle lines. This is obtained by applying a Gaussian filter and dilation on the image in E. G. The final lines obtained are superimposed on the vessel in yellow. These are the lines used to measure the diameter of the vessel.