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双混合伪标签框架:加强对类别不平衡的CT体积的半监督细分

Luyang Zhang1, Yuichiro Hayashi2, Masahiro Oda2,3

  • 1Graduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, 464-8601, Nagoya, Aichi, Japan. lzhang@mori.m.is.nagoya-u.ac.jp.

International journal of computer assisted radiology and surgery
|February 11, 2025
PubMed
概括

本研究引入了一种新的方法,通过考虑类别难度,使用有限的标记数据来改进CT图像细分. 该方法提高了医疗成像中具有挑战性的类别的细分精度.

关键词:
CT 分段化 CT 分段化不平衡的数据集半监督学习 半监督学习

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Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...