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4D Mathematical Observer Models for the Task-Based Evaluation of Gated Myocardial Perfusion SPECT Images

机译:4D数学观测器模型的门控心肌灌注SPECT图像的任务评估

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We developed and evaluated two 4D mathematical observer models for the detection of motion defects in simulated 4D gated myocardial perfusion (GMP) SPECT images, and compare predictions of the models with results from human observers. For the first model, we extended the application of conventional channelized Hotelling observer (CHO) method which uses 2D spatial channels to 4D motion images. For the second model, we developed a set of 'space-time channels' which includes a set of 2D spatial channels and an additional 1D channel in the time direction. To evaluate the models, we used the 4D eXtended CArdiac Torsro (XCAT) phantom and created 16 gates/cardiac cycle with normal myocardial perfusion but a regional wall motion defect (RWMD). Simulated GMP SPECT projection data were generated using an analytical projector and reconstructed using FBP followed by spatial and temporal low-pass filtering with various cut-off frequencies. For the first model, we extracted 2D slices from each time frame containing the defect center and produced feature vectors using the 2D channels. Then, they were stacked for all the time frames to which the ROC methodology was applied. For the second model, the extracted 2D image slices were reorganized into a set of cine 2D images and the space-time channels were applied to produce space-time feature vectors to which the ROC was applied. For both models, the rating data were analyzed and areas under the ROC curve (AUCs) were computed. The resulting AUC values of the second model showed better agreement to those previously obtained from a human observer study viewing the same data than those from the first model, and positive correlation in ranking between them was found. We have demonstrated that RWMD detection was affected by post-filtering. The AUC values from the proposed 4D space-time CHO model show good agreement with that from a human observer study in detecting a RWMD in the same set of simulated 4D GMP SPECT images.
机译:我们开发并评估了两个4D数学观察模型,用于检测模拟的4D门控心肌灌注(GMP)SPECT图像中的运动缺陷,并与人类观察者的结果进行比较模型的预测。对于第一种模型,我们扩展了使用2D空间通道的传统信道的热灵位观测器(CHO)方法的应用到4D运动图像。对于第二种模型,我们开发了一组“时空通道”,其包括一组2D空间通道和时方向上的附加1D通道。为了评估模型,我们使用了4D扩展心脏扭转(Xcat)幽灵,并创建了16个门/心脏周期,具有正常的心肌灌注,但区域墙壁运动缺陷(RWMD)。模拟GMP SPECT投影数据使用分析投影仪生成并使用FBP重建,然后使用各种截止频率进行空间和时间低通滤波。对于第一个模型,我们从包含缺陷中心的每个时间帧提取2D切片,并使用2D通道产生特征向量。然后,它们被堆叠用于应用ROC方法的所有时间框架。对于第二模型,将提取的2D图像切片重新组织成一组Cine 2D图像,并且施加空间通道以产生施加ROC的时空特征向量。对于两种模型,分析了评级数据,计算了ROC曲线(AUC)下的区域。第二模型的所得到的AUC值对先前从人类观察者研究获得的那些比来自第一模型的数据相同的数据显示了更好的同意,并且发现它们之间排名中的正相关性。我们已经证明RWMD检测受到过滤后的影响。来自所提出的4D时空CO CO模型的AUC值与来自人类观察者在同一组模拟的4DMPP SPECT图像中检测RWMD的人类观察者的研究表现出良好的一致性。

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