antithetic
发表于 2025-3-21 19:52:46
书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0264622<br><br> <br><br>书目名称Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0264622<br><br> <br><br>
institute
发表于 2025-3-21 20:49:45
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衰弱的心
发表于 2025-3-22 01:42:59
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aptitude
发表于 2025-3-22 04:35:35
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Hemiparesis
发表于 2025-3-22 12:26:13
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使混合
发表于 2025-3-22 14:42:42
https://doi.org/10.1007/978-90-481-8544-3rovided partial atlas and allows these labels to be propagated throughout the target image via block-matching. Using this technique we segmented brains of 22 subjects and compared its performance to expert ground truths. When provided with an atlas for which only 2% of voxels were labelled, this ach
使混合
发表于 2025-3-22 20:40:26
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鸣叫
发表于 2025-3-22 23:28:33
https://doi.org/10.1007/978-3-319-40667-1 synthesized images. We validate our proposed algorithm on three popular image synthesis tasks, including brain MR-to-CT, prostate MR-to-CT, and brain 3T-to-7T. The experimental results demonstrate that our proposed method can achieve good synthesis performance by using the unpaired data only.
Urea508
发表于 2025-3-23 01:53:18
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support4th International Wo
Bureaucracy
发表于 2025-3-23 08:17:36
A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentamprove the segmentation accuracy. The proposed method is evaluated over an echo cine dataset of 566 patients. Experiments show that the proposed system can reach a noticeably high mean accuracy of 97.9%, and mean Dice score of 92.7% for LV segmentation in A4C view.