Channelized Hotelling observers for the assessment of volumetric imaging data sets
Channelized Hotelling observers for the assessment of volumetric imaging data sets
复制标题
DOI：
10.1364/josaa.28.001145
复制
发表时间：
2011-06-01
影响因子：
1.9
通讯作者：
Philips, Wilfried
中科院分区：
文献类型：
--
作者：
Platisa, Ljiljana;Goossens, Bart;Philips, Wilfried
目前的临床实践正迅速向体积成像的方向发展。对于二维(2D)图像，通常使用数值模型观察器来评估基于任务的医学图像质量。然而，对于三维(3D)图像，到目前为止，这些模型还很少被探索。在这项工作中，首先，针对3D图像中的3D信号检测任务，提出了两种新的设计方案：多层信道化霍特林观测器。然后在五种不同的CHO设计的模拟研究中对新设计进行了比较和评估：单层模型、三层多层模型和体积模型。考虑了四种不同的随机背景统计量，既有高斯(不相关和相关的高斯噪声)，也有非高斯(块状和簇状块状背景)。实验结果表明，体积模型的检测效果优于其他模型，但随着检测任务的复杂程度增加，模型间的差异减小。在多切片模型中，第二种新的CHO最接近体积模型，而第一种新的CHO受训练样本数量的影响似乎最小。(C)2011年美国光学学会
Current clinical practice is rapidly moving in the direction of volumetric imaging. For two-dimensional (2D) images, task-based medical image quality is often assessed using numerical model observers. For three-dimensional (3D) images, however, these models have been little explored so far. In this work, first, two novel designs of a multislice channelized Hotelling observer (CHO) are proposed for the task of detecting 3D signals in 3D images. The novel designs are then compared and evaluated in a simulation study with five different CHO designs: a single-slice model, three multislice models, and a volumetric model. Four different random background statistics are considered, both Gaussian (noncorrelated and correlated Gaussian noise) and non-Gaussian (lumpy and clustered lumpy backgrounds). Overall, the results show that the volumetric model outperforms the others, while the disparity between the models decreases for greater complexity of the detection task. Among the multislice models, the second proposed CHO could most closely approach the volumetric model, whereas the first new CHO seems to be least affected by the number of training samples. (C) 2011 Optical Society of America