生气地
发表于 2025-3-23 12:48:03
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FAWN
发表于 2025-3-23 15:08:02
Aude Bernardaging annotations from one modality to be useful in other modalities. More specifically, the proposed algorithm creates highly realistic synthetic CT images (SynCT) from prostate MR images using unpaired data sets. By using SynCT images (without segmentation labels) and MR images (with segmentation
最有利
发表于 2025-3-23 19:24:07
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BIPED
发表于 2025-3-23 23:54:00
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Nomadic
发表于 2025-3-24 04:50:08
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放纵
发表于 2025-3-24 06:31:07
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originality
发表于 2025-3-24 12:53:58
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Notify
发表于 2025-3-24 15:15:43
Aude Bernard tasks. Despite improved performance, UNet++ introduces densely connected decoding blocks, some of which, however, are redundant for a specific task. In this paper, we propose .-UNet++ that allows us to automatically identify and discard redundant decoding blocks without the loss of precision. To th
孵卵器
发表于 2025-3-24 20:46:19
Aude Bernardifficulty of data sharing between institutions. However, contemporary multi-site techniques such as weight averaging and cyclic weight transfer make theoretical sacrifices to simplify implementation. In this paper, we implement federated gradient averaging (FGA), a variant of federated learning with
平项山
发表于 2025-3-25 00:03:47
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