Optimizing breast-tomosynthesis acquisition parameters with scanning model observers

Optimizing breast-tomosynthesis acquisition parameters with scanning model observers
复制标题

使用扫描模型观察器优化乳腺断层合成采集参数

DOI:
--
复制
发表时间:
2008
期刊:
SPIE Medical Imaging
影响因子:
--
通讯作者:
S. Glick
S. Glick
中科院分区:
--
文献类型:
--
作者:
H. Gifford;C. Didier;C. Didier;M. Das;S. Glick

文献摘要

参考文献

被引文献

相似文献

在乳房断层合成(BT)中,在有限的角度范围内获得的多个X射线投影被重建以产生三维(3D)体积。与传统的乳房X光检查相比,这种3D图像可以减少结构掩蔽效应。因此,人们对优化与BT相关的采集和重建参数非常感兴趣。在这项工作中,我们评估了扫描模型观测器和定位ROC(LROC)方法的使用,以执行基于任务的优化的角度跨度和投影角的数量模拟BT系统。将该观测器应用于经滤波反投影重建的3D体积的提取切片。本研究同时进行了“确切背景已知”(BKE)和“准背景已知”(QBKE)任务。后一任务试图通过在检测任务中保留结构噪声来解决有限的观察者训练。减少更少投影形式的噪音对于BKE任务来说很重要,尽管更大的角度跨度也是有利的。较高的采样密度可能会提高更逼真的QBKE任务的性能。
In breast tomosynthesis (BT), multiple x-ray projections obtained over a limited angular span are reconstructed to produce a three-dimensional (3D) volume. This 3D imagery can lead to reduced structural masking effects compared to conventional mammography. Accordingly, there has been considerable interest in optimizing acquisition and reconstruction parameters associated with BT. In this work, we evaluate the use of a scanning model observer and localization ROC (LROC) methodology for performing a task-based optimization of the angular span and number of projection angles for a simulated BT system. The observer was applied to extracted slices of 3D volumes reconstructed with filtered backprojection. Both "background-known-exactly" (BKE) and "quasi-BKE" (QBKE) tasks were conducted. The latter task attempts to account for limited observer training by preserving structural noise in the detection task. Reduced noise in the form of fewer projections was important with the BKE task, although wider angular spans were also advantageous. Higher sampling densities may improve performance for the more-realistic QBKE tasks.
DOI: 10.1364/josaa.18.000473
发表时间: 2001-03-01
影响因子: 1.9
作者:
Abbey, CK;Barrett, HH
通讯作者: Barrett, HH
用于优化乳腺断层合成系统的计算机模拟平台。
DOI: 10.1118/1.2558160
发表时间: 2007
期刊: Medical physics
影响因子: 3.8
作者:
Zhou,Jun;Zhao,Bo;Zhao,Wei
通讯作者: Zhao,Wei