Atlas-based linear volume-of-interest (ABL-VOI) image correction
Atlas-based linear volume-of-interest (ABL-VOI) image correction
复制标题
基于图集的线性感兴趣体积 (ABL-VOI) 图像校正
DOI：
10.1117/12.2006843
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
J. Hornegger
中科院分区：
文献类型：
--
作者：
A. Maier;Z. Jiang;J. Jordan;C. Riess;H. Hofmann;J. Hornegger
感兴趣体积成像提供了以全扫描剂量的一部分对小体积进行成像的能力。不涉及先验知识的重建方法能够恢复几乎无伪影的图像。虽然图像看起来是正确的，但它们通常会遇到这样的问题，即丢失了全扫描中包含的低频信息。这通常可以被观察为重建的对象密度的缩放误差。由于该误差取决于对象和相应扫描中的截断，因此只有具有关于对象范围的正确信息的算法才能够正确地重建密度值。在本文中，我们研究了一种方法来恢复丢失的低频信息。我们假设正确的缩放可以通过对象密度的线性变换来建模。为了确定正确的缩放比例，我们采用正确缩放体积的图谱。从图集和给定的重建体积中，我们提取相互匹配的基于块的特征。这样做，我们得到了图谱图像和重建VOI之间的对应关系，允许估计线性变换。我们研究了该方法的几种情况：在关闭条件下，我们假设患者的先前扫描已经可用。在开放条件测试中，我们从匹配过程中排除了相应患者的数据。在六个数据集中，全视图和截断数据之间的原始偏移平均为133 HU。重建中的平均噪声为140 HU。在关闭条件下，我们能够估计该缩放高达9 HU，并且在打开条件下，我们仍然可以估计偏移高达23 HU。
Volume-of-interest imaging offers the ability to image small volumes at a fraction of the dose of a full scan. Reconstruction methods that do not involve prior knowledge are able to recover almost artifact-free images. Although the images appear correct, they often suffer from the problem that low-frequency information that would be included in a full scan is missing. This can often be observed as a scaling error of the reconstructed object densities. As this error is dependent on the object and the truncation in the respective scan, only algorithms that have the correct information about the extent of the object are able to reconstruct the density values correctly. In this paper, we investigate a method to recover the lost low-frequency information. We assume that the correct scaling can be modeled by a linear transformation of the object densities. In order to determine the correct scaling, we employ an atlas of correctly scaled volumes. From the atlas and the given reconstruction volume, we extract patch-based features that are matched against each other. Doing so, we get correspondences between the atlas images and the reconstruction VOI that allow the estimation of the linear transform. We investigated several scenarios for the method: In closed condition, we assumed that a prior scan of the patient was already available. In the open condition test, we excluded the respective patient’s data from the matching process. The original offset between the full view and the truncated data was 133 HU on average in the six data sets. The average noise in the reconstructions was 140 HU. In the closed condition, we were able to estimate this scaling up to 9 HU and in open condition, we still could estimate the offset up to 23 HU.
登录
查看更多内容
用于呼吸运动补偿心脏 CArm CT 的隔膜跟踪
DOI：
--
发表时间：
2012
期刊：
影响因子：
--
作者：
Marco Bögel;A. Maier;H. Hofmann;J. Hornegger;R. Fahrig
通讯作者：
R. Fahrig
4 使用稀疏水平约束压缩感知的 DCT 重建
DOI：
--
发表时间：
2012
期刊：
影响因子：
--
作者：
Haibo Wu;A. Maier;H. Hofmann;R. Fahrig;J. Hornegger
通讯作者：
J. Hornegger
影响因子：
3.8
作者：
Fahrig, Rebecca;Dixon, Robert;Strobel, Norbert
通讯作者：
Strobel, Norbert
影响因子：
3.8
作者：
Maier, Andreas;Wigstrom, Lars;Fahrig, Rebecca
通讯作者：
Fahrig, Rebecca
用于锥束 VOI 重建的高效 2D 滤波
DOI：
10.1109/nssmic.2012.6551549
发表时间：
2012
期刊：
2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC)
影响因子：
--
作者：
Yan Xia;A. Maier;F. Dennerlein;H. Hofmann;J. Hornegger
通讯作者：
J. Hornegger