Evaluation of multiclass model observers in PET LROC studies
Evaluation of multiclass model observers in PET LROC studies
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DOI：
10.1109/tns.2006.889163
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发表时间：
2007-02-01
影响因子：
1.8
通讯作者：
King, M. A.
中科院分区：
文献类型：
--
作者：
Gifford, H. C.;Kinahan, P. E.;King, M. A.
进行了定位ROC（LROC）研究，以评估非预白化匹配滤波器（NPW）和通道化NPW（CNPW）版本的多类模型观察者作为PET图像人类肿瘤检测性能的预测因子。目标定位是明确地执行这些模型观察员。肿瘤被放置在肝脏、肺和数学体模的背景软组织中，并且数据模拟对全3D采集模式进行建模。重建采用了SVM +AWOSEM算法。LROC研究测量了观察者对同一组病例的2D图像（包括冠状面、矢状面或横断面）的表现。CNPW观察员的两个先前发表的高斯差分信道模型的基础上的版本表现出良好的定量协议与人类观察员。这些结果的一个解释对待CNPW观察员作为一个通道化的霍特林观察员与隐式内部噪声。
A localization ROC (LROC) study was conducted to evaluate nonprewhitening matched-filter (NPW) and channelized NPW (CNPW) versions of a multiclass model observer as predictors of human tumor-detection performance with PET images. Target localization is explicitly performed by these model observers. Tumors were placed in the liver, lungs, and background soft tissue of a mathematical phantom, and the data simulation modeled a full-3D acquisition mode. Reconstructions were performed with the FORE+AWOSEM algorithm. The LROC study measured observer performance with 2D images consisting of either coronal, sagittal, or transverse views of,the same set of cases. Versions of the CNPW observer based on two previously published difference-of-Gaussian channel models demonstrated good quantitative agreement with human observers. One interpretation of these results treats the CNPW observer as a channelized Hotelling observer with implicit internal noise.