迅速 发表于 2025-3-21 18:07:11
书目名称Information Processing in Medical Imaging影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0465155<br><br> <br><br>书目名称Information Processing in Medical Imaging读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0465155<br><br> <br><br>ILEUM 发表于 2025-3-21 22:33:27
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Conference proceedings 2017sions. They were organized in topical sections named: analysis on manifolds; shape analysis; disease diagnosis/progression; brain networks an connectivity; diffusion imaging; quantitative imaging; imaging genomics; image registration; segmentation; general image analysis..guzzle 发表于 2025-3-22 11:34:05
0302-9743 ical Imaging, IPMI 2017, held at the Appalachian State University, Boon, NC, USA, in June 2017. .The 53 full papers presented in this volume were carefully reviewed and selected from 147 submissions. They were organized in topical sections named: analysis on manifolds; shape analysis; disease diagnoBAN 发表于 2025-3-22 16:01:28
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Kernel Methods for Riemannian Analysis of Robust Descriptors of the Cerebral Cortex implicit lifting map to a reproducing kernel Hilbert space, and (ii) regression against clinical variables, using .. For both methods, we employ kernels that exploit the Riemannian structure. Results on simulated and clinical data shows the improved accuracy and stability of our approach in cortical-sheet analysis.Yourself 发表于 2025-3-22 22:36:35
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Stochastic Development Regression on Non-linear Manifoldsection of the manifold. We propose an estimation procedure which applies the Laplace approximation of the likelihood function. A simulation study of the performance of the model is performed and the model is applied to a real dataset of Corpus Callosum shapes.oxidize 发表于 2025-3-23 07:48:14
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