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In order to reduce the interference of noise and uneven distribution of gray level in low dose chest CT images while segmenting pulmonary nodules, this paper proposed a new segmentation method. The method incorporated a fuzz)' speed function into the active contour model, based on fuzzy membership degree, to be the evolution limit weight factor, which could e-liminate the interference of noise and other factors, as well as improve the evolution efficiency. Aiming at juxta-vascular nodules, the method fixed the membership degree by introducing a vessel characteristic coefficient to depress the influence of a plenty of vessel regions in the lung parenchyma. After experimental verification, the algorithm can improve the accuracy of the pulmonary nodules segmentation effectively and work better for juxta-vascular nodules. Besides, it also can reduce the error segmentation rate of obviously. [ABSTRACT FROM AUTHOR]