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Towards a Noninvasive Intracranial Tumor Irradiation Using 3D Optical Imaging and Multimodal Data Registration

机译:迈向使用3D光学成像和多模式数据配准的无创颅内肿瘤照射

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Conformal radiotherapy (CRT) results in high-precision tumor volume irradiation. In fractioned radiotherapy (FRT), lesions are irradiated in several sessions so that healthy neighbouring tissues are better preserved than when treatment is carried out in one fraction. In the case of intracranial tumors, classical methods of patient positioning in the irradiation machine coordinate system are invasive and only allow for CRT in one irradiation session. This contribution presents a noninvasive positioning method representing a first step towards the combination of CRT and FRT. The 3D data used for the positioning is point clouds spread over the patient's head (CT-data usually acquired during treatment) and points distributed over the patient's face which are acquired with a structured light sensor fixed in the therapy room. The geometrical transformation linking the coordinate systems of the diagnosis device (CT-modality) and the 3D sensor of the therapy room (visible light modality) is obtained by registering the surfaces represented by the two 3D point sets. The geometrical relationship between the coordinate systems of the 3D sensor and the irradiation machine is given by a calibration of the sensor position in the therapy room. The global transformation, computed with the two previous transformations, is sufficient to predict the tumor position in the irradiation machine coordinate system with only the corresponding position in the CT-coordinate system. Results obtained for a phantom show that the mean positioning error of tumors on the treatment machine isocentre is 0.4 mm. Tests performed with human data proved that the registration algorithm is accurate (0.1 mm mean distance between homologous points) and robust even for facial expression changes.
机译:适形放疗(CRT)可实现高精度的肿瘤体积照射。在分级放疗(FRT)中,要分几次照射病灶,因此与一小部分进行治疗相比,可以更好地保存健康的邻近组织。对于颅内肿瘤,在放射机坐标系统中定位患者的经典方法是侵入性的,并且仅允许在一个放射疗程中进行CRT。这一贡献提出了一种非侵入性的定位方法,代表了CRT和FRT结合的第一步。用于定位的3D数据是散布在患者头部的点云(通常在治疗过程中获取的CT数据)和散布在患者面部的点,这些点是通过固定在治疗室中的结构化光传感器获取的。通过记录由两个3D点集表示的表面,可以获得将诊断设备的坐标系统(CT模态)和治疗室的3D传感器(可见光模态)联系起来的几何变换。 3D传感器和辐照机的坐标系之间的几何关系由治疗室中传感器位置的校准给出。用前两个变换计算出的全局变换足以预测肿瘤在辐射机坐标系中的位置,而仅在CT坐标系中具有相应的位置。对于幻像获得的结果表明,肿瘤在治疗机等中心线上的平均定位误差为0.4 mm。使用人体数据进行的测试证明,该配准算法准确(同源点之间的平均距离为0.1 mm)并且即使面部表情变化也很稳定。

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