Published June 1, 2019 | Version v1
Journal article

A neural lens for super-resolution biological imaging

  • 1. Optoelectronics Research Centre, University of Southampton, Southampton, SO17 1BJ (United Kingdom)
  • 2. Department of Physics and Astronomy, University of Southampton, Southampton, SO17 1BJ (United Kingdom)
  • 3. Faculty of Medicine, University of Southampton, Southampton, SO17 1BJ (United Kingdom)

Description

Visualizing structures smaller than the eye can see has been a driving force in scientific research since the invention of the optical microscope. Here, we use a network of neural networks to create a neural lens that has the ability to transform 20× optical microscope images into a resolution comparable to a 1500× scanning electron microscope image. In addition to magnification, the neural lens simultaneously identifies the types of objects present, and hence can label, colour-enhance and remove specific types of objects in the magnified image. The neural lens was used for the imaging of Iva xanthiifolia and Galanthus pollen grains, showing the potential for low cost, non-destructive, high-resolution microscopy with automatic image processing. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/2399-6528/ab267d

Additional details

Identifiers

Publishing Information

Journal Title
Journal of Physics Communications
Journal Volume
3
Journal Issue
6
Journal Page Range
[7 p.]
ISSN
2399-6528

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52021051
Subject category
S60: APPLIED LIFE SCIENCES; S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
COLOR; IMAGE PROCESSING; IMAGES; LENSES; NEURAL NETWORKS; OPTICAL MICROSCOPES; POLLEN; SCANNING ELECTRON MICROSCOPY
Descriptors DEC
ELECTRON MICROSCOPY; GAMETES; GERM CELLS; MICROSCOPES; MICROSCOPY; OPTICAL PROPERTIES; ORGANOLEPTIC PROPERTIES; PHYSICAL PROPERTIES; PROCESSING