Dual-Mode Restoration Microscopy for Optical Aberration Correction

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Solution Overview

Problem

Oblique angle illumination microscopes suffer from reduced effective numerical aperture and optical aberrations due to the reimaging step, limiting their use for light-sensitive applications and spatial resolution, particularly when using high-magnification objectives.

Innovation Solution

A microscope system configured to operate in multiple imaging modes, utilizing a first and second reimaging objective with adjustable angles and a machine learning method, specifically a trained deep learning network, to correct optical aberrations and enhance optical resolution.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If oblique angle illumination is used with high-magnification objectives, then imaging capability is improved, but effective numerical aperture is reduced

Engineering Contradiction:
Improveimaging capabilityVSAvoideffective numerical aperture
Core Design Contradiction:
Measurement precisionVSReliability

Solution Approach 1:

The patent introduces a second spatial dimension by tilting the detection path at a reimaging angle relative to the illumination path. This dimensional change allows the detection objective to capture a larger portion of the light cone from high-NA objectives while maintaining oblique illumination geometry, thereby recovering effective numerical aperture that would otherwise be lost.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The system employs adjustable reimaging angle capability, allowing the detection path to be dynamically optimized. This dynamic adjustment enables the microscope to adapt the detection geometry to match the illumination conditions and sample requirements, maximizing light collection efficiency and effective numerical aperture across different imaging scenarios.

Inventive Principle:
Principle #15Dynamics

2Manufacturing precision

If reimaging step is introduced to correct oblique illumination, then optical quality is improved, but light collection is reduced

Engineering Contradiction:
Improveoptical qualityVSAvoidlight collection
Core Design Contradiction:
Manufacturing precisionVSLoss of energy

Solution Approach 1:

By introducing a reimaging angle that tilts the detection path out of the sample plane, the system creates an additional spatial dimension for light collection. This allows the detection objective to access light rays that would otherwise be blocked or miss the detector, thereby improving both optical quality and light collection efficiency simultaneously.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

3Measurement precision

If non-neutral magnification is applied to increase resolution, then image distortion increases

Engineering Contradiction:
Improvespatial resolutionVSAvoidimage distortion
Core Design Contradiction:
Measurement precisionVSShape

Solution Approach 1:

The tilted detection path at a reimaging angle provides an additional degree of freedom in the optical geometry. This extra dimension allows the system to achieve non-neutral magnification for enhanced resolution while the tilted geometry compensates for and corrects image distortion, maintaining proper spatial relationships in the final image.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

Data Source

PatentEP4107569B1Dual-mode restoration microscopy
Publication Date: 2025.10.22 CHARITE UNIVS MEDIZIN BERLIN
  • EP4107569B1 patent drawingFigure 1
  • EP4107569B1 patent drawingFigure 2
  • EP4107569B1 patent drawingFigure 3(A)~3(C)

AI summary

A microscope system (100) configured to record images in at least a first and a second imaging mode (501, 502), comprising: An objective (1) collecting light (201) from a sample (11), An illumination module coupled to the objective, A first reimaging objective (5) generating an intermediate image of the sample and a second reimaging objective (6) that relays the intermediate image onto a detection module, An evaluation module (200) comprising a machine learning method (DL), trained with a first and a second set of images of the same sample, wherein the first and second set has been acquired in the first (501) and second imaging mode (502), respectively, wherein upon acquisition of an image (400) in the second imaging mode (502) the trained machine learning method (DL) outputs a restored image (401) that comprises fewer aberrations than the image (400) acquired in the second imaging mode (52, 53, 57).