Background: A common problem in medical practice is the localization of subcutaneous veins and arteries. Automatization of this procedure may help to develop bloodbot rigs and improve use of image guided surgery.
Method: It is not necessary to have a full 3D model in order to determine their location by calculating the spatial coordinates of veins axes in the adopted coordinate system. A much better solution is pre-segmentation, which provides veins axes, and further search for stereo correspondence in the segmented images. The computational complexity of this approach is much smaller, which ensures its quick operation. A disparity map necessary for the calculation of spatial coordinates is created according to the principle that the most likely correct distance between homologous elements is the minimum distance value. To increase the effectiveness of the method, the difference in the distance between the homologous points and their neighbours is further analysed.
Results: The method is illustrated with examples of the authors' own images of subcutaneous veins as well as standard images used for the evaluation of new methods for seeking stereo correspondence. In addition, the method has been compared with three recognized and widely used algorithms for matching images. The effectiveness of the new method reaches 100% of properly matched pixels. The largest percentage of mismatches is 27%. The lowest value of standard deviation is 0.1 and the highest 10 pixels. The proposed method is at least two times faster than other presented methods.
Keywords: Binarization; Matching; Stereovision; Veins segmentation.
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