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基于植入基准标记的容积图像自动配准

Automatic coregistration of volumetric images based on implanted fiducial markers.

作者信息

Koch Martin, Maltz Jonathan S, Belongie Serge J, Gangadharan Bijumon, Bose Supratik, Shukla Himanshu, Bani-Hashemi Ali R

机构信息

Oncology Care Systems Group, Siemens Medical Solutions USA, Inc., 4040 Nelson Avenue, Concord, California 94520, USA.

出版信息

Med Phys. 2008 Oct;35(10):4513-23. doi: 10.1118/1.2975153.

Abstract

The accurate delivery of external beam radiation therapy is often facilitated through the implantation of radio-opaque fiducial markers (gold seeds). Before the delivery of each treatment fraction, seed positions can be determined via low dose volumetric imaging. By registering these seed locations with the corresponding locations in the previously acquired treatment planning computed tomographic (CT) scan, it is possible to adjust the patient position so that seed displacement is accommodated. The authors present an unsupervised automatic algorithm that identifies seeds in both planning and pretreatment images and subsequently determines a rigid geometric transformation between the two sets. The algorithm is applied to the imaging series of ten prostate cancer patients. Each test series is comprised of a single multislice planning CT and multiple megavoltage conebeam (MVCB) images. Each MVCB dataset is obtained immediately prior to a subsequent treatment session. Seed locations were determined to within 1 mm with an accuracy of 97 +/- 6.1% for datasets obtained by application of a mean imaging dose of 3.5 cGy per study. False positives occurred in three separate instances, but only when datasets were obtained at imaging doses too low to enable fiducial resolution by a human operator, or when the prostate gland had undergone large displacement or significant deformation. The registration procedure requires under nine seconds of computation time on a typical contemporary computer workstation.

摘要

通过植入不透射线的基准标记物(金种子)通常有助于精确实施外照射放疗。在每次治疗分次前,可通过低剂量容积成像确定种子位置。通过将这些种子位置与先前获取的治疗计划计算机断层扫描(CT)扫描中的相应位置进行配准,就可以调整患者位置以适应种子位移。作者提出了一种无监督自动算法,该算法可识别计划图像和预处理图像中的种子,并随后确定两组图像之间的刚性几何变换。该算法应用于十例前列腺癌患者的成像系列。每个测试系列由单次多层计划CT和多个兆伏级锥束(MVCB)图像组成。每个MVCB数据集在随后的治疗疗程前立即获取。对于通过每次研究平均成像剂量3.5 cGy获得的数据集,种子位置确定在1毫米以内,准确率为97±6.1%。在三个不同实例中出现了假阳性,但仅当以过低的成像剂量获取数据集以至于人工操作员无法分辨基准标记物时,或者当前列腺发生了较大位移或显著变形时。在典型的当代计算机工作站上,配准过程所需的计算时间不到9秒。

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