A Fusion Model of MRI Deep Transfer Learning and Radiomics for Discriminating between Pilocytic Astrocytoma and Adamantinomatous Craniopharyngioma.

Journal: Academic radiology
PMID: 39690073

Abstract

RATIONALE AND OBJECTIVES: This study aimed to develop and validate a fusion model combining MRI deep transfer learning (DTL) and radiomics for discriminating between pilocytic astrocytoma (PA) and adamantinomatous craniopharyngioma (ACP) in the sellar region.

Authors

  • Yu Mao
    Department of Radiology, The Affiliated Hospital of Southwest Medical University, No. 23 Tai Ping Street, Luzhou, 646000, Sichuan, China.
  • Xin Kong
    Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (Y.M., X.K., Y.L., F.X., Y.L., J.M.). Electronic address: 874807413@qq.com.
  • Yuqi Luo
    Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (Y.M., X.K., Y.L., F.X., Y.L., J.M.). Electronic address: yqluo92@163.com.
  • Fengjun Xi
    Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (Y.M., X.K., Y.L., F.X., Y.L., J.M.). Electronic address: 18702625936@163.com.
  • Yan Li
    Interdisciplinary Research Center for Biology and Chemistry, Liaoning Normal University, Dalian, China.
  • Jun Ma
    State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China.

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