Project overview

A self-learning microscope image analysis tool designed to identify immunofluorescence labeled cells for more efficient diagnostics of tumors. Pre-trained neural network solution able to recognize different types of blood cells by analyzing imagery acquired from microscopes.

Key features and highlights

  • Providing the exact location of the target cells in clinical images
  • Drastically cutting the time needed for pathogenic cell identification
  • Improving the accuracy and efficiency of molecular diagnostics
  • Analyzing microscope images to identify immunofluorescence labeled tumor cells
  • Continuous improvement with as the machine learning-based component processes new input