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Trachea segmentation in CT images using active contours

Tracheal stenosis is an uncommon pathology that in early stages is often confused with different respiratory affections by its signs and symptoms. An automatic characterization of the tracheal stenosis requires adequate medical images and efficient segmentation algorithms. In CT images, several algorithms of airway segmentation have been used, such as 3D region growing, thresholding and gray-level profile analysis. In this work a segmentation method for trachea extraction in CT images is proposed. The algorithm is based on an active contour model (SS) formulated by considering the explicit expression of the natural cubic splines and is compared with the original snakes model (OS). In both cases, an automatic definition of the initial contour based on a Canny filter is proposed. Eight images were processed with both algorithms and the results show that the SS model is less sensitive to initial conditions. For this image modality the Canny operator proved to be a good choice to obtain the initial contour. The SS method generates a smoothed version of the tracheal border.