Di-chromatic interpolation of magnetic resonance metabolic images.

Di-chromatic interpolation of magnetic resonance metabolic images.
复制标题

DOI:
10.1007/s10334-020-00903-y
复制
发表时间:
2021-03
期刊:
Magma (New York, N.Y.)
影响因子:
--
通讯作者:
Larson PEZ
Larson PEZ
中科院分区:
其他
文献类型:
--
作者:
Dwork N;Gordon JW;Tang S;O'Connor D;Hansen ESS;Laustsen C;Larson PEZ

文献摘要

参考文献

相似文献

使用超极化造影剂的磁共振成像可以提供前所未有的体内新陈代谢测量,但产生的图像分辨率低于质子解剖成像。为了在空间上定位代谢活动,必须将代谢图像内插到质子图像的大小。选择未知值的最常见方法完全依赖于原始未内插图像的值。在这项工作中,我们提出了一种替代方法,使用更高分辨率的质子图像来提供额外的空间结构。该内插图像是凸优化算法的结果,该算法用快速迭代收缩阈值算法(FISTA)来求解。结果显示了超极化的丙酮酸、乳酸和碳酸氢盐的图像,使用的数据来自健康的人类志愿者、健康的猪心脏和前列腺癌患者的心脏和大脑。
Magnetic resonance imaging with hyperpolarized contrast agents can provide unprecedented in-vivo measurements of metabolism, but yields images that are lower resolution than that achieved with proton anatomical imaging. In order to spatially localize the metabolic activity, the metabolic image must be interpolated to the size of the proton image. The most common methods for choosing the unknown values rely exclusively on values of the original un-interpolated image. In this work, we present an alternative method that uses the higher-resolution proton image to provide additional spatial structure. The interpolated image is the result of a convex optimization algorithm which is solved with the Fast Iterative Shrinkage Threshold Algorithm (FISTA). Results are shown with images of hyperpolarized pyruvate, lactate, and bicarbonate using data of the heart and brain from healthy human volunteers, a healthy porcine heart, and a human with prostate cancer.
DOI: 10.1007/s001580050111
发表时间: 1999-10-01
期刊: STRUCTURAL OPTIMIZATION
影响因子: --
作者:
Das, I
通讯作者: Das, I
DOI: 10.1016/j.jmr.2008.03.012
发表时间: 2008-07-01
影响因子: 2.2
作者:
Cunningham, Charles H.;Chen, Albert P.;Vigneron, Daniel B.
通讯作者: Vigneron, Daniel B.
DOI: 10.1007/978-1-84800-155-8_7
发表时间: 2008-01-01
期刊: RECENT ADVANCES IN LEARNING AND CONTROL
影响因子: --
作者:
Grant, Michael C.;Boyd, Stephen P.
通讯作者: Boyd, Stephen P.
DOI: 10.1137/080716542
发表时间: 2009-01-01
影响因子: 2.1
作者:
Beck, Amir;Teboulle, Marc
通讯作者: Teboulle, Marc
DOI: 10.1109/tmi.2016.2564989
发表时间: 2017-01
影响因子: 10.6
作者:
Knoll F;Holler M;Koesters T;Otazo R;Bredies K;Sodickson DK
通讯作者: Sodickson DK