本文提出一种消除磁共振图像截断伪影的新方法。
A new method of truncation MR artifact reduction is proposed in this paper.
最后的实验使用男人脑部电磁共振图像支持了这种发现。
A final experiment using magnetic resonance imaging (MRI) of the men's brains backed up this finding.
目的选择合适的脉冲线圈以获得清晰的腹部磁共振图像。
Objective To obtain high quality of abdomen image by selecting proper RF coils.
在实验前后，科学家都给受试者拍了大脑的磁共振图像。
The scientists took MRI images of the subjects' brains before and after the experiment.
目的：设计适用于颅脑磁共振图像分割的神经网络算法。
Objective Designing segmentation of brain MRIs based on neural networks.
研究者收集这些儿童在6岁和9岁的详细的核磁共振图像。
The researchers collected detailed magnetic resonance images of the children's brains at age 6 and again at 9.
本文提出一种适合于含有截断伪影磁共振图像的边缘检测新算法。
We propose a new edge detection algorithm suited to MR images with truncation artifact.
磁共振图像细节丰富，且灰度变化细微的区域也反映了不同组织。
Detail is abundant in MRI image and the trifle difference in the gray scale denotes different structure.
本文提出了一种适合于含有截断伪影磁共振图像的边缘检测新算法。
In this paper, we propose a new edge finding technology to fit to MR images with truncation artifact.
进行头模型构建的前提就是人头部磁共振图像脑轮廓的提取和分割问题。
To constructing real head models, the problem of brain contour finding from head MRI images must be solved.
带标记线核磁共振图像是精确研究心肌形变以及心肌质点运动的重要途径。
Using tagged Magnetic Resonance (MR) images, we can research deformation and motion of the heart muscle.
目的介绍一种动态模糊聚类算法并利用该算法对磁共振图像进行分割研究。
Objective to introduce a dynamic fuzzy clustering algorithm and use it to do the study of segmentation of the brain in MRI.
多个组织参数被从要被分类的图像数据(例如磁共振图像数据)中提取出来。
A plurality of tissue parameters are extracted from image data (e. g., magnetic resonance image data) to be classified.
在实际的脑部核磁共振图像上进行实验，文中算法可以准确地分割出脑部肿瘤。
The proposed method is used to brain magnetic resonance images, it can segment the tumor correctly.
而且，这些方法将组织分割问题表述成组织磁共振图像中像素不同成分的有限集合。
And those methods addressed the problems of tissue segmentation as the partitioning concourse of the components in a pixel in finite sets.
本文分析磁共振图像上几种特殊的装备伪影的表现及形成原因，探讨消除伪影的方法。
Analyzes the performances and causes of artifacts related to some special equipment on MR images and discusses the method of the troubleshooting for artifacts.
多年来，对心脏核磁共振图像(MRI)的分析研究一直是医学图像领域的一个重要课题。
Research on cardiac MR image (MRI) analysis is a significant topic in the field of medical image for many years.
空间分辨率是衡量磁共振图像的重要指标，它直接影响到图像质量的好坏以及图像的诊断价值。
The image space resolution ratio is the most important index to evaluate the images of MRI.
由于受带标记线心脏核磁共振图像中标记线强梯度的影响，对左心室内膜的提取变得非常困难。
However, affected by the strong gradient from tagged lines in tagged cardiac MR images, extracting endocardium boundaries makes itself very difficult.
图像均匀度是衡量磁共振图像的重要指标，它直接影响到图像质量的好坏以及图像的诊断价值。
The image uniformity is an important index to evaluate the quality of MRI image. It affect the the quality of the image and the clinical diagnostic value of the image.
本发明公开了一种对扩散张量磁共振图像进行恢复处理的方法，涉及医疗诊断图像处理技术领域。
The invention discloses a method for recovery processing of a diffusion tensor magnetic resonance image, relating to the medical diagnosis image processing technical field.
根据脑肿瘤在核磁共振图像上的梯度以及图像中点的强度分布提出了一种新的基于水平集的分割方法。
Proposed a new brain tumor segmentation method based on the level set method using the gradient and the intensity distribution information in magnetic resonance images.
目的对基于数学形态学的磁共振图像局部对比度增强算法进行临床MR图像测试，为完善算法提供依据。
Objective To improve the new algorithm of local contrast enhancement for MR image based on mathematical morphology, we evaluated the performance of the algorithm by real MR images from clinical use.
所使用的图像数据可以是在嗜淋巴细胞的超顺磁毫微粒的静脉给药之前以及之后所获得的磁共振图像数据。
The image data used may be magnetic resonance image data that was obtained before and after the intravenous administration of lymphotropic superparamagnetic nanoparticles.
磁共振图像的准确分割对于辅助医生确定病灶的位置和形状、制订治疗方案和评价治疗效果具有重要的意义。
Correct segmentation of magnetic resonance image (MRI) is very important for doctors to ascertain the shape and position of the focus, prepare cure scheme and evaluate cure effect.
获得并处理所说的磁共振信号，以便形成至少两个磁共振图像，每个磁共振图像都对应于所说激励触发角之一。
MR signals are acquired and processed so as to form at least two MR images, each corresponding to one of these flip angles.
神经网络具有类似人脑的并行处理结构，能够模拟人脑对刺激的反应方式进行工作，可以用于解决磁共振图像分割问题。
With the parallel structure like the human brain, neural networks can simulate the reaction of brain which is stimulated, and can be applied for MRI segmentation.
神经网络具有类似人脑的并行处理结构，能够模拟人脑对刺激的反应方式进行工作，可以用于解决磁共振图像分割问题。
With the parallel structure like the human brain, neural networks can simulate the reaction of brain which is stimulated, and can be applied for MRI segmentation.
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