:

Alessia De Biase1, Liv Ziegfeld2, Nanna Maria Sijtsema3

  • 1Department of Radiation Oncology, University Medical Center Groningen (UMCG), 9700 RB, Groningen, the Netherlands; Data Science Center in Health (DASH), University Medical Center Groningen (UMCG), 9700 RB, Groningen, the Netherlands.

概括

深度学习生成的瘤概率图为头癌细分提供了直观和可解释的替代方案,改善了放射瘤学家的工作流程. 这种方法增强了瘤自我细分模型的概括性.

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