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Accelerating whole-sample polarization-resolved second harmonic generation imaging in mammary gland tissue via generative adversarial networks.

Arash AghighJysiane CardotMelika Saadat MohammadiGaëtan JargotHeide IbrahimIsabelle PlanteFrançois Légaré
Published in: Biomedical optics express (2024)
Polarization second harmonic generation (P-SHG) imaging is a powerful technique for studying the structure and properties of biological and material samples. However, conventional whole-sample P-SHG imaging is time consuming and requires expensive equipment. This paper introduces a novel approach that significantly improves imaging resolution under conditions of reduced imaging time and resolution, utilizing enhanced super-resolution generative adversarial networks (ESRGAN) to upscale low-resolution images. We demonstrate that this innovative approach maintains high image quality and analytical accuracy, while reducing the imaging time by more than 95%. We also discuss the benefits of the proposed method for reducing laser-induced photodamage, lowering the cost of optical components, and increasing the accessibility and applicability of P-SHG imaging in various fields. Our work significantly advances whole-sample mammary gland P-SHG imaging and opens new possibilities for scientific discovery and innovation.
Keyphrases
  • high resolution
  • magnetic resonance imaging
  • small molecule
  • machine learning
  • fluorescence imaging