Deep learning-based multi-model approach on electron microscopy image of renal biopsy classification.

Journal: BMC nephrology
Published Date:

Abstract

BACKGROUND: Electron microscopy is important in the diagnosis of renal disease. For immune-mediated renal disease diagnosis, whether the electron-dense granule is present in the electron microscope image is of vital importance. Deep learning methods perform well at feature extraction and assessment of histologic images. However, few studies on deep learning methods for electron microscopy images of renal biopsy have been published. This study aimed to develop a deep learning-based multi-model to automatically detect whether the electron-dense granule is present in the TEM image of renal biopsy, and then help diagnose immune-mediated renal disease.

Authors

  • Jingyuan Zhang
    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China.
  • Aihua Zhang
    College of Chinese Medicinal Materials, Jilin Agricultural University, Changchun, China.