Automatic identification of suspicious bone metastatic lesions in bone scintigraphy using convolutional neural network.

Journal: BMC medical imaging
Published Date:

Abstract

BACKGROUND: We aimed to construct an artificial intelligence (AI) guided identification of suspicious bone metastatic lesions from the whole-body bone scintigraphy (WBS) images by convolutional neural networks (CNNs).

Authors

  • Yemei Liu
    Laboratory of Clinical Nuclear Medicine, Department of Nuclear Medicine, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China.
  • Pei Yang
    Department of Bone and Joint Surgery, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Yong Pi
    Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, 610065, PR China.
  • Lisha Jiang
    Laboratory of Clinical Nuclear Medicine, Department of Nuclear Medicine, West China Hospital of Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, People's Republic of China.
  • Xiao Zhong
    Laboratory of Clinical Nuclear Medicine, Department of Nuclear Medicine, West China Hospital of Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, People's Republic of China.
  • Junjun Cheng
    Laboratory of Clinical Nuclear Medicine, Department of Nuclear Medicine, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China.
  • Yongzhao Xiang
    Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, PR China.
  • Jianan Wei
    Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, 610065, People's Republic of China.
  • Lin Li
    Department of Medicine III, LMU University Hospital, LMU Munich, Munich, Germany.
  • Zhang Yi
  • Huawei Cai
    Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, PR China. Electronic address: hw.cai@yahoo.com.
  • Zhen Zhao