提出了一种分析多层印刷电路板电源分配网络(power distribution network,PDN)中一维(1D)介质型电磁带隙(electromagnetic band-gap,EBG)结构噪声隔离性能的1D有限元数值计算方法.将1D介质型EBG的3D结构简化为1D有限元模型,通过直接求...提出了一种分析多层印刷电路板电源分配网络(power distribution network,PDN)中一维(1D)介质型电磁带隙(electromagnetic band-gap,EBG)结构噪声隔离性能的1D有限元数值计算方法.将1D介质型EBG的3D结构简化为1D有限元模型,通过直接求解波动方程获得传输系数T、反射系数R以及散射参数S.利用R-T曲线可直观地判定频率禁带,而采用分贝表示的S21参数则更方便评价噪声隔离度.根据介质型EBG的周期数、介电常数和周期长度等参数对噪声隔离性能影响的仿真结果,针对少周期、不完全禁带EBG结构提出了先采用多周期EBG结构预测禁带,再通过调整介电常数和周期长度扩展禁带和增强噪声隔离度的两阶段设计方法.采用3D全波电磁仿真验证了1D有限元算法的合理性.展开更多
Similarity coefficient mapping（SCM） aims to improve the morphological evaluation of T＊2weighted magnetic resonance imaging（T＊2-w MRI）. However, how to interpret the generated SCM map is still pending. Moreover, ...Similarity coefficient mapping（SCM） aims to improve the morphological evaluation of T＊2weighted magnetic resonance imaging（T＊2-w MRI）. However, how to interpret the generated SCM map is still pending. Moreover, is it probable to extract tissue dissimilarity messages based on the theory behind SCM？ The primary purpose of this paper is to address these two questions. First, the theory of SCM was interpreted from the perspective of linear fitting. Then, a term was embedded for tissue dissimilarity information. Finally, our method was validated with sixteen human brain image series from multiecho T＊2-w MRI. Generated maps were investigated from signal-to-noise ratio（SNR） and perceived visual quality, and then interpreted from intra- and inter-tissue intensity. Experimental results show that both perceptibility of anatomical structures and tissue contrast are improved. More importantly, tissue similarity or dissimilarity can be quantified and cross-validated from pixel intensity analysis. This method benefits image enhancement, tissue classification, malformation detection and morphological evaluation.展开更多
The purpose of this paper is to investigate the feasibility of using a similarity coefficient map（SCM） in improving the morphological evaluation of T2＊ weighted（T2＊W） magnatic resonance imaging（MRI） for renal ...The purpose of this paper is to investigate the feasibility of using a similarity coefficient map（SCM） in improving the morphological evaluation of T2＊ weighted（T2＊W） magnatic resonance imaging（MRI） for renal cancer.Simulation studies and in vivo 12-echo T2＊W experiments for renal cancers were performed for this purpose.The results of the first simulation study suggest that an SCM can reveal small structures which are hard to distinguish from the background tissue in T2＊W images and the corresponding T2＊ map.The capability of improving the morphological evaluation is likely due to the improvement in the signal-to-noise ratio（SNR） and the carrier-to-noise ratio（CNR） by using the SCM technique.Compared with T2＊ W images,an SCM can improve the SNR by a factor ranging from 1.87 to 2.47.Compared with T2＊ maps,an SCM can improve the SNR by a factor ranging from 3.85 to 33.31.Compared with T2＊W images,an SCM can improve the CNR by a factor ranging from 2.09 to 2.43.Compared with T2＊ maps,an SCM can improve the CNR by a factor ranging from 1.94 to 8.14.For a given noise level,the improvements of the SNR and the CNR depend mainly on the original SNRs and CNRs in T2＊W images,respectively.In vivo experiments confirmed the results of the first simulation study.The results of the second simulation study suggest that more echoes are used to generate the SCM,and higher SNRs and CNRs can be achieved in SCMs.In conclusion,an SCM can provide improved morphological evaluation of T2＊W MR images for renal cancer by unveiling fine structures which are ambiguous or invisible in the corresponding T2＊W MR images and T2＊ maps.Furthermore,in practical applications,for a fixed total sampling time,one should increase the number of echoes as much as possible to achieve SCMs with better SNRs and CNRs.展开更多
文摘提出了一种分析多层印刷电路板电源分配网络(power distribution network,PDN)中一维(1D)介质型电磁带隙(electromagnetic band-gap,EBG)结构噪声隔离性能的1D有限元数值计算方法.将1D介质型EBG的3D结构简化为1D有限元模型,通过直接求解波动方程获得传输系数T、反射系数R以及散射参数S.利用R-T曲线可直观地判定频率禁带,而采用分贝表示的S21参数则更方便评价噪声隔离度.根据介质型EBG的周期数、介电常数和周期长度等参数对噪声隔离性能影响的仿真结果,针对少周期、不完全禁带EBG结构提出了先采用多周期EBG结构预测禁带,再通过调整介电常数和周期长度扩展禁带和增强噪声隔离度的两阶段设计方法.采用3D全波电磁仿真验证了1D有限元算法的合理性.
基金Project supported in part by the National High Technology Research and Development Program of China(Grant Nos.2015AA043203 and 2012AA02A604)the National Natural Science Foundation of China(Grant Nos.81171402+8 种基金61471349and 81501463)the Innovative Research Team Program of Guangdong Province,China(Grant No.2011S013)the Science and Technological Program for Higher Education,Science and Researchand Health Care Institutions of Guangdong ProvinceChina(Grant No.2011108101001)the Natural Science Foundation of Guangdong Province,China(Grant No.2014A030310360)the Fundamental Research Program of Shenzhen City,China(Grant No.JCYJ20140417113430639)Beijing Center for Mathematics and Information Interdisciplinary Sciences,China
文摘Similarity coefficient mapping（SCM） aims to improve the morphological evaluation of T＊2weighted magnetic resonance imaging（T＊2-w MRI）. However, how to interpret the generated SCM map is still pending. Moreover, is it probable to extract tissue dissimilarity messages based on the theory behind SCM？ The primary purpose of this paper is to address these two questions. First, the theory of SCM was interpreted from the perspective of linear fitting. Then, a term was embedded for tissue dissimilarity information. Finally, our method was validated with sixteen human brain image series from multiecho T＊2-w MRI. Generated maps were investigated from signal-to-noise ratio（SNR） and perceived visual quality, and then interpreted from intra- and inter-tissue intensity. Experimental results show that both perceptibility of anatomical structures and tissue contrast are improved. More importantly, tissue similarity or dissimilarity can be quantified and cross-validated from pixel intensity analysis. This method benefits image enhancement, tissue classification, malformation detection and morphological evaluation.
基金Project supported by the National Basic Research Program of China (Grant No. 2011CB707701)the National Key Technology R&D Program of China(Grant Nos. 2011BAI12B05 and 2012BAI23B07)
文摘The purpose of this paper is to investigate the feasibility of using a similarity coefficient map（SCM） in improving the morphological evaluation of T2＊ weighted（T2＊W） magnatic resonance imaging（MRI） for renal cancer.Simulation studies and in vivo 12-echo T2＊W experiments for renal cancers were performed for this purpose.The results of the first simulation study suggest that an SCM can reveal small structures which are hard to distinguish from the background tissue in T2＊W images and the corresponding T2＊ map.The capability of improving the morphological evaluation is likely due to the improvement in the signal-to-noise ratio（SNR） and the carrier-to-noise ratio（CNR） by using the SCM technique.Compared with T2＊ W images,an SCM can improve the SNR by a factor ranging from 1.87 to 2.47.Compared with T2＊ maps,an SCM can improve the SNR by a factor ranging from 3.85 to 33.31.Compared with T2＊W images,an SCM can improve the CNR by a factor ranging from 2.09 to 2.43.Compared with T2＊ maps,an SCM can improve the CNR by a factor ranging from 1.94 to 8.14.For a given noise level,the improvements of the SNR and the CNR depend mainly on the original SNRs and CNRs in T2＊W images,respectively.In vivo experiments confirmed the results of the first simulation study.The results of the second simulation study suggest that more echoes are used to generate the SCM,and higher SNRs and CNRs can be achieved in SCMs.In conclusion,an SCM can provide improved morphological evaluation of T2＊W MR images for renal cancer by unveiling fine structures which are ambiguous or invisible in the corresponding T2＊W MR images and T2＊ maps.Furthermore,in practical applications,for a fixed total sampling time,one should increase the number of echoes as much as possible to achieve SCMs with better SNRs and CNRs.
