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Updated: Jan 10, 2026

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

修正:RSA-TransUNet:一个强大的结构适应性TransUNet,用于增强道路裂细分

Liling Hou¹, Fei Yu^2,3,4, Yaowen Hu⁵

¹Zhangzhou Institute of Technology, Zhangzhou, China.

Frontiers in neurorobotics

|November 26, 2025

概括

这项研究纠正了先前发表的一篇文章. 校正确保了准确的引用和数据完整性,用于该领域未来的研究.

科学领域:

神经科学是一个神经科学.
计算生物学计算生物学

背景情况:

计算神经科学领域的先前研究需要准确的引用.
确保数据完整性对于可重复的科学发现至关重要.

研究的目的:

为了纠正某一特定出版物的文章DOI.
维护科学文献的准确性和可追溯性.

主要方法:

发出了一份正式的纠正通知.
数字物体标识符 (DOI) 在出版记录中得到更新.

主要成果:

文章DOI已经正式纠正.
修正后的DOI确保了正确的引用和对研究的访问.

结论:

准确的DOI对科学界至关重要.
这次纠正符合科学出版的标准.

关键词:

适应式线条线性单元线性单元轴转移MLP注意力轴转移MLP注意力进化优化的进化优化道路裂纹细分道路裂纹细分结构意识的多阶段结构意识.

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