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    • 3. 发明申请
    • Terminal Power Control Method
    • 端子功率控制方法
    • US20080212548A1
    • 2008-09-04
    • US11915114
    • 2006-05-15
    • Jianxun SunYong FanTiezhu XuGang Niu
    • Jianxun SunYong FanTiezhu XuGang Niu
    • H04B7/216
    • H04W52/24H04W52/343
    • A terminal power control method includes following steps according to the quality of received signal, the terminal obtains quality parameter of received signal, received power of terminal occupying channel, and all the channel power in present cell which have the same carrier frequency and time slot with terminal occupying channel respectively; according to all the channel power in present cell which have the same carrier frequency and time slot with terminal occupying channel, determines the allowable received power minimum of terminal occupying channel; according to the allowable received power minimum of terminal occupying channel, received power of said terminal occupying channel and said received signal quality parameters, generates power control command. Present invention could control powers of signals in different channels, increase the demodulation performance of terminal and the stability of wireless link, and assure the quality of system communication.
    • 终端功率控制方法包括根据接收信号质量的以下步骤,终端获取接收信号的质量参数,终端占用信道的接收功率,以及具有相同载波频率和时隙的当前小区中的所有信道功率, 终端占用通道; 根据具有终端占用信道相同载波频率和时隙的本小区的所有信道功率,确定终端占用信道的允许接收功率最小值; 根据终端占用信道的允许接收功率最小值,所述终端占用信道的接收功率和接收到的信号质量参数,生成功率控制命令。 本发明可以控制不同信道的信号功率,提高终端的解调性能和无线链路的稳定性,保证系统通信的质量。
    • 4. 发明授权
    • Method and system for brain tumor segmentation in multi-parameter 3D MR images via robust statistic information propagation
    • 通过鲁棒统计信息传播,在多参数三维MR图像中进行脑肿瘤分割的方法和系统
    • US09129382B2
    • 2015-09-08
    • US13000255
    • 2010-06-25
    • Yong FanHongming Li
    • Yong FanHongming Li
    • G06K9/00G06T7/00
    • G06T7/0081G06T7/11G06T7/143G06T7/162G06T2207/10088G06T2207/20081G06T2207/30016G06T2207/30096
    • A method for brain tumor segmentation in multi-parametric 3D MR images. The method comprises: pre-processing an input multi-parametric 3D MR image; classifying each voxel in the pre-processed multi-parametric 3D MR image, determining the probability that the voxel is part of a brain tumor, and obtaining an initial label information for the image segmentation based on the classification probability; constructing a graph based representation for the pre-processed image to be segmented; and generating the segmented brain tumor image using the initial label information and graph based representation. This method tries to exploit the local and global consistency of the image to be segmented for the tumor segmentation and can alleviate partially the performance degradation caused by the inter-subject image variability and insufficient statistical information from training.
    • 一种多参数三维MR图像中脑肿瘤分割的方法。 该方法包括:对输入的多参数3D MR图像进行预处理; 对预处理的多参数3D MR图像中的每个体素进行分类,确定体素是脑肿瘤一部分的可能性,并且基于分类概率获得用于图像分割的初始标签信息; 构建要分割的预处理图像的基于图形的表示; 并使用初始标签信息和基于图形的表示来产生分割的脑肿瘤图像。 该方法试图利用分割图像的局部和全局一致性进行肿瘤分割,并可以部分减轻受试者图像变异性引起的性能下降和培训不足的统计信息。
    • 5. 发明授权
    • Method for registering functional MRI data
    • 功能性MRI数据记录方法
    • US08965093B2
    • 2015-02-24
    • US13806509
    • 2011-12-21
    • Yong FanDi JiangTianzi Jiang
    • Yong FanDi JiangTianzi Jiang
    • G06T7/00
    • G06T7/0012G06T7/33G06T2200/04G06T2207/10088G06T2207/30016
    • A method for registering functional MRI data, comprising: computing the functional connectivity pattern for every voxel in its given spatial neighborhood for every fMRI image; extracting features invariant to spatial location of the neighboring voxels based on the functional connectivity patterns; constructing similarity metric between voxels of different images based on the extracted features, and using fluid-like demons registration model to spatial normalize the fMRI data. The present invention tries to exploit the multi-range functional connectivity information of the fMRI data, and to register functional MR images based on the extracted spatial-location-invariant features. The present invention is robust against local spatial perturbations and does not depend on the assumption that functional signals of different subjects are synchronic, hence can be applied to resting-state fMRI data, and can achieve a statistically significant improvement in functional consistency across subjects.
    • 一种用于登记功能性MRI数据的方法,包括:为每个fMRI图像计算其给定空间邻域中的每个体素的功能连接性模式; 基于功能连通性模式提取不相邻体素空间位置的特征; 基于提取的特征构建不同图像的体素之间的相似性度量,并使用流体样恶魔注册模型对fMRI数据进行空间归一化。 本发明试图利用fMRI数据的多范围功能连接性信息,并且基于所提取的空间位置不变特征来注册功能性MR图像。 本发明对于局部空间扰动是鲁棒的,并且不依赖于不同主体的功能信号是同步的假设,因此可以应用于静息状态的fMRI数据,并且可以实现主体之间的功能一致性的统计学显着的改善。
    • 6. 发明授权
    • Method for brain tumor segmentation in multi-parametric image based on statistical information and multi-scale structure information
    • 基于统计信息和多尺度结构信息的多参数图像脑肿瘤分割方法
    • US08908948B2
    • 2014-12-09
    • US13806493
    • 2011-12-21
    • Yong FanHongming Li
    • Yong FanHongming Li
    • G06K9/00G06T7/00
    • G06T7/0081G06T7/11G06T7/143G06T2207/10088G06T2207/20076G06T2207/20081G06T2207/30016G06T2207/30096Y10S128/922
    • A method for brain tumor segmentation in multi-parametric 3D magnetic resonance (MR) images, comprising: determining, for each voxel in the multi-parametric 3D MR image sequence, a probability that the voxel is part of brain tumor; extracting multi-scale structure information of the image; generating multi-scale tumor probability map based on initial tumor probability at voxel level and multi-scale structure information; determining salient tumor region based on multi-scale tumor probability map; obtaining robust initial tumor and non-tumor label based on tumor probability map at voxel level and salient tumor region; and generating a segmented brain tumor image using graph based label information propagation. The present invention is capable of achieving statistical reliable, spatially compact, and robust tumor label initialization, which is helpful to the accurate and reliable tumor segmentation. And the label information propagation framework could partially alleviate the performance degradation caused by image inconsistency between images to be segmented and training images.
    • 一种用于多参数三维磁共振(MR)图像中的脑肿瘤分割的方法,包括:针对多参数3D MR图像序列中的每个体素,确定体素是脑肿瘤一部分的概率; 提取图像的多尺度结构信息; 根据体素水平的初始肿瘤概率和多尺度结构信息生成多尺度肿瘤概率图; 基于多尺度肿瘤概率图确定显着肿瘤区域; 基于体素水平和显着肿瘤区域的肿瘤概率图获得稳健的初始肿瘤和非肿瘤标志物; 并使用基于图的标签信息传播产生分割的脑肿瘤图像。 本发明能够实现统计可靠,空间紧凑,鲁棒的肿瘤标签初始化,有助于准确可靠的肿瘤分割。 标签信息传播框架可以部分缓解由要分割的图像与训练图像之间的图像不一致引起的性能下降。
    • 8. 发明申请
    • METHOD FOR BRAIN TUMOR SEGMENTATION IN MULTI-PARAMETRIC IMAGE BASED ON STATISTICAL INFORMATION AND MULTI-SCALE STRUTURE INFORMATION
    • 基于统计信息和多尺度信息信息的多参数图像中脑肿瘤分期的方法
    • US20130182931A1
    • 2013-07-18
    • US13806493
    • 2011-12-21
    • Yong FanHongming Li
    • Yong FanHongming Li
    • G06T7/00
    • G06T7/0081G06T7/11G06T7/143G06T2207/10088G06T2207/20076G06T2207/20081G06T2207/30016G06T2207/30096Y10S128/922
    • A method for brain tumor segmentation in multi-parametric 3D magnetic resonance (MR) images, comprising: determining, for each voxel in the multi-parametric 3D MR image sequence, a probability that the voxel is part of brain tumor; extracting multi-scale structure information of the image; generating multi-scale tumor probability map based on initial tumor probability at voxel level and multi-scale structure information; determining salient tumor region based on multi-scale tumor probability map; obtaining robust initial tumor and non-tumor label based on tumor probability map at voxel level and salient tumor region; and generating a segmented brain tumor image using graph based label information propagation. The present invention is capable of achieving statistical reliable, spatially compact, and robust tumor label initialization, which is helpful to the accurate and reliable tumor segmentation. And the label information propagation framework could partially alleviate the performance degradation caused by image inconsistency between images to be segmented and training images.
    • 一种用于多参数三维磁共振(MR)图像中的脑肿瘤分割的方法,包括:针对多参数3D MR图像序列中的每个体素,确定体素是脑肿瘤一部分的概率; 提取图像的多尺度结构信息; 根据体素水平的初始肿瘤概率和多尺度结构信息生成多尺度肿瘤概率图; 基于多尺度肿瘤概率图确定显着肿瘤区域; 基于体素水平和显着肿瘤区域的肿瘤概率图获得稳健的初始肿瘤和非肿瘤标志物; 并使用基于图的标签信息传播产生分割的脑肿瘤图像。 本发明能够实现统计可靠,空间紧凑,鲁棒的肿瘤标签初始化,有助于准确可靠的肿瘤分割。 标签信息传播框架可以部分缓解由要分割的图像与训练图像之间的图像不一致引起的性能下降。
    • 9. 发明申请
    • METHOD FOR REGISTERING FUNCTION MRI DATA
    • 注册功能MRI数据的方法
    • US20130177228A1
    • 2013-07-11
    • US13806509
    • 2011-12-21
    • Yong FanDi JiangTianzi Jiang
    • Yong FanDi JiangTianzi Jiang
    • G06T7/00
    • G06T7/0012G06T7/33G06T2200/04G06T2207/10088G06T2207/30016
    • A method for registering functional MRI data, comprising: computing the functional connectivity pattern for every voxel in its given spatial neighborhood for every fMRI image; extracting features invariant to spatial location of the neighboring voxels based on the functional connectivity patterns; constructing similarity metric between voxels of different images based on the extracted features, and using fluid-like demons registration model to spatial normalize the fMRI data. The present invention tries to exploit the multi-range functional connectivity information of the fMRI data, and to register functional MR images based on the extracted spatial-location-invariant features. The present invention is robust against local spatial perturbations and does not depend on the assumption that functional signals of different subjects are synchronic, hence can be applied to resting-state fMRI data, and can achieve a statistically significant improvement in functional consistency across subjects.
    • 一种用于登记功能性MRI数据的方法,包括:为每个fMRI图像计算其给定空间邻域中的每个体素的功能连接性模式; 基于功能连通性模式提取不相邻体素空间位置的特征; 基于提取的特征构建不同图像的体素之间的相似性度量,并使用流体样恶魔注册模型对fMRI数据进行空间归一化。 本发明试图利用fMRI数据的多范围功能连接性信息,并且基于所提取的空间位置不变特征来注册功能性MR图像。 本发明对于局部空间扰动是鲁棒的,并且不依赖于不同主体的功能信号是同步的假设,因此可以应用于静息状态的fMRI数据,并且可以实现主体之间的功能一致性的统计学显着的改善。
    • 10. 发明授权
    • Method and system for providing fast design for testability prototyping in integrated circuit designs
    • 用于为集成电路设计中的可测试性原型设计提供快速设计的方法和系统
    • US07134106B2
    • 2006-11-07
    • US10821505
    • 2004-04-09
    • Steve C. HuangYong FanIhao Chen
    • Steve C. HuangYong FanIhao Chen
    • G06F11/00G06F17/50
    • G06F17/5045G06F17/5031G06F2217/14
    • Method and system for providing a computer implemented process of performing design for testability analysis and synthesis in an integrated circuit design includes partitioning each logic block in an integrated circuit design based on one or more boundaries of multi-cycle initial setup sequence, excluding one or more partitioned logic blocks with multi-cycle initial setup sequence from valid candidate blocks, selecting a constraint setting set, extracting a subset of constraint settings from the selected constraint setting set, applying the extracted subset of constraint settings to the integrated circuit design, performing design for testability analysis and synthesis on the valid candidate blocks, performing scan cell replacement. The scan cell replacement may include performing class selection from a cell library and a gate-level netlist based on affinity between cells, determining a target characterization, such as timing, power, area, for example, for the scan cell replacement, and replacing one or more cells with a corresponding one or more scan cells having the closest target characteristics.
    • 用于提供在集成电路设计中执行用于可测试性分析和合成的设计的计算机实现过程的方法和系统包括基于多周期初始设置序列的一个或多个边界来划分集成电路设计中的每一个逻辑块,不包括一个或多个 分区逻辑块,具有来自有效候选块的多循环初始设置序列,选择约束设置集合,从所选择的约束设置集中提取约束设置的子集,将所提取的约束设置的子集应用于集成电路设计,执行设计 对有效候选块进行可测试性分析和综合,执行扫描单元更换。 扫描单元替换可以包括基于小区之间的亲和度从小区库和门级网表执行类选择,确定目标表征,例如定时,功率,区域,例如用于扫描小区替换,以及替换一个 或具有相应的一个或多个具有最接近的目标特征的扫描单元的单元。