Human- and model-observer performance in ramp-spectrum noise: effects of regularization and object variability
Human- and model-observer performance in ramp-spectrum noise: effects of regularization and object variability
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DOI：
10.1364/josaa.18.000473
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发表时间：
2001-03-01
影响因子：
1.9
通讯作者：
Barrett, HH
中科院分区：
文献类型：
--
作者：
Abbey, CK;Barrett, HH
我们考虑在有噪图像中检测结节信号轮廓，旨在粗略模拟核医学中断层图像重建的统计特性。图像有两个来源的变异性所产生的量子噪声从成像过程和解剖变异性的整体对象被成像。这两个来源的可变性模拟一个平稳的高斯随机过程。通过过滤白噪声图像来生成来自该过程的样本图像。通过心理物理学研究，使用两种选择的强迫选择方法，在几个信号已知的检测任务中，人类观察者的表现进行了评估。所考虑的任务调查的图像的参数，影响信号的轮廓和像素到像素的相关性的图像。低通滤波的效果进行了研究，作为一个近似的正则化实现的图像重建算法。的量子和解剖变异的相对幅度进行了研究，作为一个近似的曝光时间的影响。最后，我们研究了解剖学相关性的效果，以解剖学斜率的形式作为不同组织类型的效果的近似。人类观察员的性能进行比较，直接从合奏统计的图像中使用的实验中找到预测模型的目的计算的模型观察员的数量的性能。模型观察员调查包括一些nonprewhitening观察员，霍特林观察员（这是相当于这些研究的理想观察员），和6个实现的通道化霍特林观察员。人类观察者在研究的实验参数中表现出很大的影响。在正则化研究中，性能在正则化的中间水平上表现出一个温和的峰值，然后在更高的水平上下降。曝光时间研究表明，人类观察者能够在增加曝光时间的情况下发现更细微的病变。解剖斜率研究表明，人类观察者的性能下降，解剖变异性扩展到更高的空间频率。在测试的观察者中，通道化Hotelling观察者最好地捕捉人类数据的特征。(C)2001年美国光学学会。
We consider detection of a nodule signal profile in noisy images meant to roughly simulate the statistical properties of tomographic image reconstructions in nuclear medicine. The images have two sources of variability arising from quantum noise from the imaging process and anatomical variability in the ensemble of objects being imaged. Both of these sources of variability are simulated by a stationary Gaussian random process. Sample images from this process are generated by filtering white-noise images. Human-observer performance in several signal-known-exactly detection tasks is evaluated through psychophysical studies by using the two-alternative forced-choice method. The tasks considered investigate parameters of the images that influence both the signal profile and pixel-to-pixel correlations in the images. The effect of low-pass filtering is investigated as an approximation to regularization implemented by image-reconstruction algorithms. The relative magnitudes of the quantum and the anatomical variability are investigated as an approximation to the effects of exposure time. Finally, we study the effect of the anatomical correlations in the form of an anatomical slope as an approximation to the effects of different tissue types. Human-observer performance is compared with the performance of a number of model observers computed directly from the ensemble statistics of the images used in the experiments for the purpose of finding predictive models. The model observers investigated include a number of nonprewhitening observers, the Hotelling observer (which is equivalent to the ideal observer for these studies), and six implementations of channelized-Hotelling observers. The human observers demonstrate large effects across the experimental parameters investigated. In the regularization study, performance exhibits a mild peak at intermediate levels of regularization before degrading at higher levels. The exposure-time study shows that human observers are able to detect ever more subtle lesions at increased exposure times. The anatomical slope study shows that human-observer performance degrades as anatomical variability extends into higher spatial frequencies. Of the observers tested, the channelized-Hotelling observers best capture the features of the human data. (C) 2001 Optical Society of America.