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一种减少胸部肿瘤放疗图像引导配准误差的方法 被引量:3

Study on the Method for Reducing the Image-Guided Registration Error in Thoracic Tumor Radiotherapy
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摘要 目的比较医师和技师的配准结果,分析其结果不一致的原因,并提出解决方法。方法选择胸部肿瘤病人30例123组IVS图像,每组IVS图像均用3种方式行图像匹配:A组:仅由技师自主对胸部病灶进行图像匹配;B组:仅由医生对胸部病灶进行图像匹配;C组:技师采取气管隆嵴结合主动脉弓为匹配特征点对胸部病灶进行图像匹配。对三组结果采用配对t检验。结果A与B比较,在左右位(Lateral,LAT)、背腹位(Dorsoventral,VRT)方向误差差异无统计学意义(P>0.05);在头脚位(Head Pin,LNG)方向误差差异有统计学意义(P<0.05);C与B比较,在LAT、VRT、LNG方向误差均无统计学意义(P>0.05)。结论本文提出的技师采取气管隆嵴结合主动脉弓为匹配特征点对胸部病灶进行图像匹配的方法是可行的,可以解决医师和技师配准结果不一致的问题,提高技师自主配准精度。 Objective To compare the registration results of doctors and technicians,analyze the reasons for the inconsistent results,and propose solutions.Methods A total of 123 groups of image verification system(IVS)images of 30 patients with chest tumor were selected,and each group of IVS images were matched in three ways:in group A,only the technician independently matched the images of thoracic lesions;in group B,only the doctor matched the images of thoracic lesions;in group C,the technician took the tracheal carina junction and aortic arch as the matching feature points to match the images of thoracic lesions.Paired t-test was used for the results of the three groups.Results There was no significant difference in the error of lateral(LAT),dorsoventral(VRT)direction between group A and B(P>0.05).There was significant difference in the error of head pin(LNG)direction(P<0.05).There was no significant difference between group C and B in errors of LAT,VRT and LNG direction(P>0.05).Conclusion In this paper,the technician’s image matching method using tracheal carina combined with aortic arch as the matching feature points for image matching of chest lesions is feasible,which can solve the problem of inconsistent registration results between doctors and technicians,and improve the accuracy of technician self-registration.
作者 杨定强 戴红娅 周一兵 YANG Dingqiang;DAI Hongya;ZHOU Yibing(Department of Radiotherapy,the Second Affiliated Hospital of Army Medical University,Chongqing 400037,China)
出处 《中国医疗设备》 2022年第2期57-59,69,共4页 China Medical Devices
基金 陆军军医大学科技创新能力提升专项项目(2019XLC3036)。
关键词 影像验证系统 胸部肿瘤 图像引导 匹配误差 匹配特征点 image verification system chest tumor image-guided matching error matching feature points
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