湖南大学学报（自然科学版）2016，Vol.43Issue(2)：141-149,9.
头颈部肿瘤 PET 图像分割随机游走方法
Random Walk Method for PET Image Segmentation of Head and Neck Cancer
摘要
Abstract
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 inter-est (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 di-lation 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.关键词
医学图像分割/随机游走/区域生长/生物靶区/头颈癌Key words
medical image segmentation/random walk/region growing/biological target volume/head and neck cancer分类
信息技术与安全科学引用本文复制引用
刘国才,胡泽田,朱苏雨,袁媛,刘科,吴峥,张九堂,莫逸..头颈部肿瘤 PET 图像分割随机游走方法[J].湖南大学学报（自然科学版）,2016,43(2):141-149,9.基金项目
国家自然科学基金资助项目（61271382，61301254，61471166），National Natural Science Foundation of China（61271382）；湖南省肿瘤医院科研平台建设基金项目 （）
