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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022; 25th International C Linwei Wang,Qi Dou,Shuo Li Conference procee

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樓主: 爆裂
41#
發(fā)表于 2025-3-28 16:01:00 | 只看該作者
0302-9743 reconstruction;.Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; mach978-3-031-16439-2978-3-031-16440-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
42#
發(fā)表于 2025-3-28 21:26:31 | 只看該作者
Jiayu Chen,Lei Mou,Shaodong Ma,Huazhu Fu,Lijun Guo,Yalin Zheng,Jiong Zhang,Yitian Zhao
43#
發(fā)表于 2025-3-29 01:08:31 | 只看該作者
44#
發(fā)表于 2025-3-29 06:33:46 | 只看該作者
45#
發(fā)表于 2025-3-29 07:54:14 | 只看該作者
46#
發(fā)表于 2025-3-29 12:48:47 | 只看該作者
Sunyi Zheng,Jingxiong Li,Zhongyi Shui,Chenglu Zhu,Yunlong Zhang,Pingyi Chen,Lin Yang
47#
發(fā)表于 2025-3-29 15:49:28 | 只看該作者
Medical Image Computing and Computer Assisted Intervention – MICCAI 202225th International C
48#
發(fā)表于 2025-3-29 22:35:53 | 只看該作者
An End-to-End Combinatorial Optimization Method for?R-band Chromosome Recognition with?Grouping Guidssignment module (DAM) is designed for flexible and differentiable label assignment. It exploits the aggregated features to infer class probability distributions between all chromosomes in a cell. Experimental results on both normal and numerically abnormal karyotypes confirmed that our method outpe
49#
發(fā)表于 2025-3-30 03:19:00 | 只看該作者
Efficient Biomedical Instance Segmentation via?Knowledge Distillationance-level features and instance relationships by the instance graphs built from embeddings of the teacher-student pair, respectively, and (ii) pixel affinity distillation that converts pixel embeddings into pixel affinities and explicitly transfers the structured knowledge of instance boundaries en
50#
發(fā)表于 2025-3-30 05:15:25 | 只看該作者
Tracking by?Weakly-Supervised Learning and?Graph Optimization for?Whole-Embryo , lineageshe cell tracking challenge on the . embryo dataset. We report a further extensive quantitative evaluation on two more . datasets. We will make these datasets public to serve as an extended benchmark for future method development. Our results suggest considerable improvements yielded by our method, e
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