Multiclass classification of whole-body scintigraphic images using a self-defined convolutional neural network with attention modules.

Journal: Medical physics
Published Date: Sep 14, 2021

Abstract

PURPOSE: A self-defined convolutional neural network is developed to automatically classify whole-body scintigraphic images of concern (i.e., the normal, metastasis, arthritis, and thyroid carcinoma), automatically detecting diseases with whole-body bone scintigraphy.

Authors

  • Qiang Lin
    College of Sciences, Zhejiang University of Technology, China.
  • Chuangui Cao
    School of Mathematics and Computer Science, Northwest Minzu University, No. 1, Xibei Xincun Rd., Lanzhou, 730030, Gansu, China.
  • Tongtong Li
  • Yongchun Cao
    School of Mathematics and Computer Science, Northwest Minzu University, No. 1, Xibei Xincun Rd., Lanzhou, 730030, Gansu, China.
  • Zhengxing Man
    School of Mathematics and Computer Science, Northwest Minzu University, No. 1, Xibei Xincun Rd., Lanzhou, 730030, Gansu, China.
  • Haijun Wang
    Department of Intensive Care Unit, National Cancer Center/National Clinical Research Center, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

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