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使用微软 Kinect 进行患者体型估计和辐射剂量归一化:概念验证和初步验证。

Using the Microsoft Kinect for patient size estimation and radiation dose normalization: proof of concept and initial validation.

机构信息

Department of Radiology, Hospital of the University of Pennsylvania, 1 Silverstein, 3400 Spruce Street, Philadelphia, PA 19104, USA.

出版信息

J Digit Imaging. 2013 Aug;26(4):657-62. doi: 10.1007/s10278-012-9567-2.

Abstract

Monitoring patients' imaging-related radiation is currently a hot topic, but there are many obstacles to accurate, patient-specific dose estimation. While some, such as easier access to dose data and parameters, have been overcome, the challenge remains as to how accurately these dose estimates reflect the actual dose received by the patient. The main parameter that is often not considered is patient size. There are many surrogates-weight, body mass index, effective diameter-but none of these truly reflect the three-dimensional "size" of an individual. In this work, we present and evaluate a novel approach to estimating patient volume using the Microsoft Kinect™, a combination RGB camera-infrared depth sensor device. The goal of using this device is to generate a three-dimensional estimate of patient size, in order to more effectively model the dimensions of the anatomy of interest and not only enable better normalization of dose estimates but also promote more patient-specific protocoling of future CT examinations. Preliminary testing and validation of this system reveals good correlation when individuals are standing upright with their arms by their sides, but demonstrates some variation with arm position. Further evaluation and testing is necessary with multiple patient positions and in both adult and pediatric patients. Correlation with other patient size metrics will also be helpful, as the ideal measure of patient "size" may in fact be a combination of existing metrics and newly developed techniques.

摘要

监测患者的影像学相关辐射目前是一个热门话题,但准确、个体化的剂量估计存在许多障碍。虽然已经克服了一些障碍,如更容易获得剂量数据和参数,但这些剂量估计如何准确反映患者实际接受的剂量仍然是一个挑战。通常被忽略的一个主要参数是患者的体型。有许多替代指标——体重、体重指数、有效直径——但这些都不能真正反映个体的三维“大小”。在这项工作中,我们提出并评估了一种使用 Microsoft Kinect™(一种结合 RGB 摄像头和红外深度传感器的设备)估计患者体积的新方法。使用该设备的目的是生成患者体型的三维估计,以便更有效地对感兴趣的解剖结构的尺寸进行建模,不仅能够更好地对剂量估计进行归一化,还能够促进未来 CT 检查的个体化协议制定。该系统的初步测试和验证表明,当个体直立且手臂放在身体两侧时,相关性较好,但当手臂位置发生变化时,相关性会有所不同。需要对多种患者体位和成人及儿科患者进行进一步的评估和测试。与其他患者体型指标的相关性也将有所帮助,因为患者“体型”的理想衡量标准可能实际上是现有指标和新开发技术的结合。

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