In order to solve the problem of the high accuracy delineation of biological target volume (BTV) for the radiotherapy of head and neck cancer, a random walk method was proposed by using PET (positron emission computed tomography) image features of tumors.Firstly, the selected region of interest (ROI) was segmented into the primary tumor (labeled as foreground seeds), normal tissue (labeled as background seeds) and pending region by three-dimensional adaptive region growing and morphological dilation based on PET SUV images.Secondly, due to the differences of contrast texture feature of head and neck tumor and surrounding normal tissues in PET images, the contrast texture feature was incorporated into the weights of random walk(RW) to further improve the accuracy of tumor segmentation results.Clinical PET image segmentations of head and neck cancer have shown that the improved RW is 9.34 times faster than the traditional RW on average.And the similarity is increased by 32.5% on average if the gross tumor volume delineated by clinicians is considered as the ground truth (P<0.05).The proposed method is an efficient and accurate method for the delineation of the BTV corresponding to head and neck tumors.