[Deep Learning-Based Key Frame Recognition Algorithm for Adrenal Vascular in X-Ray Imaging].

Journal: Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Published Date:

Abstract

Adrenal vein sampling is required for the staging diagnosis of primary aldosteronism, and the frames in which the adrenal veins are presented are called key frames. Currently, the selection of key frames relies on the doctor's visual judgement which is time-consuming and laborious. This study proposes a key frame recognition algorithm based on deep learning. Firstly, wavelet denoising and multi-scale vessel-enhanced filtering are used to preserve the morphological features of the adrenal veins. Furthermore, by incorporating the self-attention mechanism, an improved recognition model called ResNet50-SA is obtained. Compared with commonly used transfer learning, the new model achieves 97.11% in accuracy, precision, recall, , and AUC, which is superior to other models and can help clinicians quickly identify key frames in adrenal veins.

Authors

  • Huimin Tao
    Department of The First Clinical Medical College of Gansu, University of Chinese Medicine, Lanzhou, Gansu, China.
  • Miao Huang
  • Cong Liu
    Department of Bioengineering, University of Illinois at Chicago, 851 S Morgan St, Chicago, IL, 60607, USA.
  • Yongtian Liu
    Urinary Surgery, Shandong First Medical University Affiliated Qingzhou Hospital, Qingzhou, 262500.
  • Zhihua Hu
    School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai, 201209.
  • Lili Tao
    School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai, 201209.
  • Shuping Zhang
    School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai, 201209.