2D Swin U-Net3D U-Net,CT

Qin An1, Hirohisa Oda2, Yuichiro Hayashi1

  • 1Graduate School of Informatics, Nagoya University, Nagoya, Aichi, 4648601, Japan.

概括

这项研究提出了一种新的半监督学习方法,用于CT扫描中的肠道细分. 尽管标记数据有限,但该方法提高了准确性,提高了复杂腹部结构的细分性能.

相关概念视频

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