U-Net使

Yeonhyo Choi1, Myoung Nam Kim2, Sungdae Na3

  • 1Department of Medical & Biological Engineering, Graduate School, Kyungpook National University, Daegu 41404, Republic of Korea.

PubMed
概括

这项研究通过将Inception模块集成到U-Net架构中来增强超声图像中的乳腺癌细分. 改进的模型显示了~5%的性能提升,推进了自动化医疗图像分析.