Transfer Learning of the ResNet-18 and DenseNet-121 Model Used to Diagnose Intracranial Hemorrhage in CT Scanning.

Journal: Current pharmaceutical design
Published Date: Jan 1, 2022

Abstract

OBJECTIVE: The aim of the study was to verify the ability of the deep learning model to identify five subtypes and normal images in non-contrast enhancement CT of intracranial hemorrhage.

Authors

  • Qi Zhou
  • Wenjie Zhu
    Department of Pathology, Maternal and Child Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Fuchen Li
    College of Art and Science, Vanderbilt University, Nashville, Tennessee 37212, USA.
  • Mingqing Yuan
    Medical College of Guangxi University, Nanning, Guangxi,China.
  • Linfeng Zheng
    Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China; Department of Radiology, Shanghai First People's Hospital, Baoshan Branch, Shanghai 200940, China. Electronic address: zhenglinfeng04@aliyun.com.
  • Xu Liu
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore. liuxu16@bjut.edu.cn.

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