针对一项检测任务,联合优化视像准直器和重建参数的策略

Lili Zhou, S. Kulkarni, Bin Liu, G. Gindi
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引用次数: 10

摘要

在像SPECT这样的系统中,原始数据由成像系统获得,然后由人类观察者重建和查看。我们比较了两种方法来优化SPECT检测任务与一个已知的信号在统计变化的背景。在顺序方法中,我们使用应用于正弦图的理想观测器来优化准直器。然后,我们使用仿人信道化霍特林观测器(CHO)优化重构的正则化。在第二种方法中,我们使用CHO来联合优化准直器和正则化。联合方法的性能优于顺序方法。联合方法的准直器性质比顺序方法的准直器性质更接近于商用准直器的性质。因此,使用由理想观测器导出的“最佳”准直器会导致次优的网络检测性能。
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Strategies to jointly optimize spect collimator and reconstruction parameters for a detection task
In systems like SPECT, raw data is obtained by the imaging system and then reconstructed and viewed by a human observer. We compare two approaches to optimizing SPECT for a detection task with a known signal in a statistically varying background. In a sequential approach, we optimize the collimator using an ideal observer applied to the sinogram. We then optimize the regularization of the reconstruction using a human-emulating channelized Hotelling observer (CHO). In a second approach, we use the CHO to jointly optimize the collimator and regularization. The performance of the joint approach exceeds that of the sequential approach. The collimator properties from the joint approach are closer to that of a commercial collimator than those of the sequential approach. Thus using the “best” collimator derived by an ideal observer leads to suboptimal net detection performance.
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