A Generative Adversarial Network technique for high-quality super-resolution reconstruction of cardiac magnetic resonance images [0.03%]
用于高质量心脏磁共振图像超分辨率重建的生成对抗网络技术
Ming Zhao,Yang Wei,Kelvin K L Wong
Ming Zhao
Purpose: In this paper, we proposed a Denoising Super-resolution Generative Adversarial Network (DnSRGAN) method for high-quality super-resolution reconstruction of noisy cardiac magnetic resonance (CMR) images. ...
2D RF pulse design for optimized reduced field-of-view imaging at 1.5T and 3T [0.03%]
用于优化的减少视野成像的二维射频脉冲设计（在1.5T和3T时）
Orhun Caner Eren,Bahadir Alp Barlas,Emine Ulku Saritas
Orhun Caner Eren
Two-dimensional spatially selective radiofrequency (2DRF) excitation pulses are widely used for reduced field-of-view (FOV) targeted high-resolution diffusion weighted imaging (DWI), especially for anatomically small regions such as the spi...
Carotid arterial wall MRI of apolipoprotein e-deficient mouse at 7 T using DANTE-prepared variable-flip-angle rapid acquisition with relaxation enhancement [0.03%]
使用DANTE准备的可变翻转角度快速放松增强成像在7T下对载脂蛋白E基因敲除小鼠颈动脉壁进行MRI研究
Yuanbo Yang,Zhonghao Li,Qiang Liu et al.
Yuanbo Yang et al.
Purpose: To optimize a sequence combining the delay alternating with nutation for tailored excitation (DANTE) preparative module with the variable-flip-angle rapid acquisition with relaxation enhancement (VF-RARE) sequenc...
Gray matter structural plasticity in patients with basal ganglia germ cell tumors: A voxel-based morphometry study [0.03%]
基底节区生殖细胞瘤患者的灰质结构可塑性变化：基于体素的形态度量研究
Yanong Li,Peng Wang,Bo Li et al.
Yanong Li et al.
Background: Basal ganglia germ cell tumors (BGGCTs) are rare intracranial germ cell tumors (iGCTs) that often presents with cognitive impairment. Objectiv...
Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion [0.03%]
子宫癌预后风险因素的放射组学机器学习及其对深入肌层浸润判断的影响
Satoshi Otani,Yuki Himoto,Mizuho Nishio et al.
Satoshi Otani et al.
Purpose: To evaluate radiomic machine learning (ML) classifiers based on multiparametric magnetic resonance images (MRI) in pretreatment assessment of endometrial cancer (EC) risk factors and to examine effects on radiolo...
Evaluating potential of multi-parametric MRI using co-registered histology: Application to a mouse model of glioblastoma [0.03%]
评价多参数MRI的潜力使用配准组织学：胶质母细胞瘤小鼠模型中的应用
H Al-Mubarak,A Vallatos,L Gallagher et al.
H Al-Mubarak et al.
Background: Conventional MRI fails to detect regions of glioblastoma cell infiltration beyond the contrast-enhanced T1 solid tumor region, with infiltrating tumor cells often migrating along host blood vessels. ...
A novel technique for automating stiffness measurement and emphasizing the main wave: Coherent-wave auto-selection (CHASE) [0.03%]
一种新的自动化刚度测量和突出主波的技术：相干波自动选择(CHASE)技术
Daiki Ito,Tomokazu Numano,Tetsushi Habe et al.
Daiki Ito et al.
This study aims to develop and assess a new automated processing technique in MR elastography (MRE), namely coherent-wave auto-selection (CHASE). CHASE enables automatic selection of the region of interest (ROI) for stiffness measurement by...
MRI-based machine learning for determining quantitative and qualitative characteristics affecting the survival of glioblastoma multiforme [0.03%]
基于MRI的机器学习在确定多形性胶质母细胞瘤生存影响的定量和定性特征中的应用
Mahdie Jajroudi,Milad Enferadi,Amir Azar Homayoun et al.
Mahdie Jajroudi et al.
Purpose: Our current study aims to consider the image biomarkers extracted from the MRI images for exploring their effects on glioblastoma multiforme (GBM) patients' survival. Determining its biomarker helps better manage...
Differential detection of metastatic and inflammatory lymph nodes using inflow-based vascular-space-occupancy (iVASO) MR imaging [0.03%]
利用基于流入的血管空间 occupancy(iVASO)磁共振成像区分转移性和炎症性淋巴结
Liuji Guo,Xiaomin Liu,Jun Hua et al.
Liuji Guo et al.
Purpose: To investigate the potential value of inflow-based vascular-space-occupancy (iVASO) MR imaging in differentiating metastatic from inflammatory lymph nodes (LNs). ...
Multiple two-dimensional active shape model framework for right ventricular segmentation [0.03%]
右心室分割的多二维主动形状模型框架
Hossam El-Rewaidy,Ahmed S Fahmy,Ayman M Khalifa et al.
Hossam El-Rewaidy et al.
Segmentation of the right ventricle (RV) in MRI short axis images is very challenging due to its complex shape and various appearance among the different subjects and cross-sections. Active shape models (ASM) have shown potential for segmen...