Technology ID

Producing Isotropic Super-Resolution Images from Line Scanning Confocal Microscopy

Lead Inventor
Shroff, Hari (NIBIB)
Wu, Yicong (NIBIB)
La Riviere, Patrick (University of Chicago)
Han, Xiaofei (NIBIB)
Software / Apps
Medical Devices
Development Stages
Pre-clinical (in vivo)
Research Products
Research Equipment
Computational models/software
Lead IC

This technology includes a microscopy technique that produces super-resolution images from diffraction-limited images obtained from a line scanning confocal microscope. First, the operation of the confocal microscope is modified so that images with sparse line excitation are recorded. Second, these images are processed to increase resolution in one dimension. Third, by taking a series of such super-resolved images from a given sample type, a neural network may be trained to produce images with 1D super-resolution from new diffraction-limited images. Finally, by rotating a given diffraction-limited image through a series of angles, passing each of these images through the trained network, and combining the resulting 1D super-resolved images with joint deconvolution, images with isotropic super-resolution may be obtained.

Commercial Applications
There are many line confocal microscopes that are currently on the market; this invention should offer better and more isotropic resolution than any of them and would thus be attractive. Furthermore, our associated machine learning algorithms could be of commercial interest, and the key steps in our invention could also be applied to other widely available and sold microscopes, including 3D structured illumination (SIM) systems, and STED systems.

Competitive Advantages
  • The ability to produce super-resolution images from diffraction-limited images is of great practical interest in cell biology, developmental biology, and neuroscience. Of note, our method produces super-resolution images with no drawback in speed or increase in dose relative to the base line confocal technique which is used to acquire the diffraction-limited data.
  • The wide number of line confocal microscopes in existence suggest that there may be broad adoption by the community.
  • The invention contains computational algorithms embedded in its very core. It will very likely provide a model for the growing field of ‘computational microscopy’ methods
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