更正：直肠癌患者的扩散加权成像：高斯模型与非高斯模型的比较
Correction: Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.
作者信息
Manikis Georgios C, Marias Kostas, Lambregts Doenja M J, Nikiforaki Katerina, van Heeswijk Miriam M, Bakers Frans C H, Beets-Tan Regina G H, Papanikolaou Nikolaos
出版信息
PLoS One. 2018 Apr 17;13(4):e0196262. doi: 10.1371/journal.pone.0196262. eCollection 2018.
Abstract
[This corrects the article DOI: 10.1371/journal.pone.0184197.].
摘要
[本文更正了文章的数字对象标识符：10.1371/journal.pone.0184197。]
相似文献
1
Correction: Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.更正：直肠癌患者的扩散加权成像：高斯模型与非高斯模型的比较
PLoS One. 2018 Apr 17;13(4):e0196262. doi: 10.1371/journal.pone.0196262. eCollection 2018.
2
Correction: Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.更正：直肠癌患者的扩散加权成像：高斯模型与非高斯模型的比较。
PLoS One. 2017 Dec 20;12(12):e0190290. doi: 10.1371/journal.pone.0190290. eCollection 2017.
3
Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI.直肠磁共振 3.0T 成像弥散加权成像中基于非高斯和高斯扩散模型的对比研究。
Sci Rep. 2016 Dec 9;6:38782. doi: 10.1038/srep38782.
4
Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.直肠癌患者的扩散加权成像：高斯模型与非高斯模型的比较
PLoS One. 2017 Sep 1;12(9):e0184197. doi: 10.1371/journal.pone.0184197. eCollection 2017.
5
Correction: Evaluation of different mathematical models and different b-value ranges of diffusion-weighted imaging in peripheral zone prostate cancer detection using b-value up to 4500 s/mm2.更正：使用高达4500 s/mm²的b值评估不同数学模型及不同b值范围的扩散加权成像在外周带前列腺癌检测中的应用
PLoS One. 2017 Sep 6;12(9):e0184609. doi: 10.1371/journal.pone.0184609. eCollection 2017.
6
Correction: Gaussian decomposition of high-resolution melt curve derivatives for measuring genome-editing efficiency.更正：用于测量基因组编辑效率的高分辨率熔解曲线导数的高斯分解
PLoS One. 2018 Mar 12;13(3):e0194470. doi: 10.1371/journal.pone.0194470. eCollection 2018.
7
Correction: Gaussian-binary restricted Boltzmann machines for modeling natural image statistics.更正：用于对自然图像统计进行建模的高斯 - 二元受限玻尔兹曼机
PLoS One. 2017 Mar 15;12(3):e0174289. doi: 10.1371/journal.pone.0174289. eCollection 2017.
8
Correction: Cerebral Hemodynamics in Patients with Hemolytic Uremic Syndrome Assessed by Susceptibility Weighted Imaging and Four-Dimensional Non-Contrast MR Angiography.更正：通过 susceptibility weighted imaging 和四维非对比磁共振血管造影评估溶血性尿毒症综合征患者的脑血流动力学
PLoS One. 2017 Feb 14;12(2):e0172450. doi: 10.1371/journal.pone.0172450. eCollection 2017.
9
Correction: Preliminary Study of MR Diffusion Tensor Imaging of Pancreas for the Diagnosis of Acute Pancreatitis.更正：胰腺磁共振扩散张量成像诊断急性胰腺炎的初步研究。
PLoS One. 2016 Oct 19;11(10):e0165353. doi: 10.1371/journal.pone.0165353. eCollection 2016.
10
Correction: correlation of the apparent diffusion coefficient (ADC) with the Standardized Uptake Value (SUV) in lymph node metastases of non-small cell lung cancer (NSCLC) patients using hybrid 18F-FDG PET/MRI.校正：使用混合18F-FDG PET/MRI对非小细胞肺癌（NSCLC）患者淋巴结转移灶中表观扩散系数（ADC）与标准化摄取值（SUV）的相关性研究
PLoS One. 2015 Mar 25;10(3):e0122545. doi: 10.1371/journal.pone.0122545. eCollection 2015.
本文引用的文献
1
Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.直肠癌患者的扩散加权成像：高斯模型与非高斯模型的比较
PLoS One. 2017 Sep 1;12(9):e0184197. doi: 10.1371/journal.pone.0184197. eCollection 2017.
Zotero 插件