Luminescence Imaging Refining Loop for Tissue Scattering

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Solution Overview

Problem

Fluorescence imaging in medical applications is limited by tissue scattering and absorption, leading to poor penetration depth and diffused images, which hinders target detection, quantification, and surgical precision.

Innovation Solution

A refining loop method using partial illuminations with spatial patterns to iteratively improve image clarity by combining component images, reducing diffusion and discriminating targets at different depths.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Length of stationary object

If NIR excitation light is used to improve penetration depth, then imaging depth increases to 1-2 cm, but tissue scattering increases causing diffused images and target intermingling

Engineering Contradiction:
Improvepenetration depthVSAvoidtissue scattering
Core Design Contradiction:
Length of stationary objectVSObject-affected harmful factors

Solution Approach 1:

The patent segments the imaging process into multiple iterations with different spatial illumination patterns. Each iteration captures component images that are later combined to form the final image. This segmentation allows the system to overcome scattering effects by accumulating signal from multiple directional illuminations rather than relying on a single illumination path.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies different spatial illumination patterns to different regions of the tissue in each iteration. By varying the illumination distribution locally across iterations and combining the results, the system enhances signal from deeper targets while suppressing scattered light contributions, effectively improving penetration depth without sacrificing image quality.

Inventive Principle:
Principle #3Local quality

2Manufacturing precision

If structured illumination is used to separate superficial and deep features, then spatial resolution improves, but image acquisition complexity increases

Engineering Contradiction:
Improvespatial resolutionVSAvoidillumination control complexity
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent employs periodic structured illumination patterns that are systematically varied across multiple iterations. These periodic patterns enable the separation of superficial and deep features through their distinct spatial frequency responses, while the iterative refinement process manages the complexity by building upon previous iterations rather than requiring all patterns simultaneously.

Inventive Principle:
Principle #19Periodic action

Solution Approach 2:

The patent incorporates a feedback mechanism where each iteration's component images are combined and used to inform subsequent illumination patterns. This feedback loop allows the system to progressively refine the illumination strategy based on previously acquired information, reducing the overall complexity by adapting to the actual tissue properties revealed in earlier iterations.

Inventive Principle:
Principle #23Feedback

3Measurement precision

If multiple spatial patterns are applied iteratively to reduce diffusion, then image quality improves, but acquisition time increases

Engineering Contradiction:
Improveimage qualityVSAvoidacquisition time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent performs preliminary actions in each iteration by capturing component images with specific spatial patterns before combining them. These preliminary captures are strategically designed to accumulate the necessary information for high-quality imaging, allowing the system to progress toward the final high-resolution image in a systematic manner that balances quality and time efficiency.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent merges component images from multiple iterations with different spatial illumination patterns to form the final combined image. This merging process consolidates the information gathered across iterations, effectively reducing diffusion effects and enhancing image quality while managing acquisition time through efficient combination algorithms.

Inventive Principle:
Principle #5Merging (Combining)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enhances image quality, facilitating accurate target detection, quantification, and surgical precision by reducing diffusion and distinguishing superficial and deep targets.

Implementation Method 1

a fluorescence phenomenon occurs in certain substances, called fluorophores, which emit light when they are illuminated

Methodology Applied
Scientific EffectFluorescence: Fluorescence

Implementation Method 2

the performance of fluorescence imaging is limited by optical properties of the tissues, i.e., scattering and absorption

Methodology Applied
Scientific EffectScattering: Scattering

Implementation Method 3

the performance of fluorescence imaging is limited by optical properties of the tissues, i.e., scattering and absorption

Methodology Applied
Scientific EffectAbsorption: Absorption (EM radiation)

Data Source

PatentEP3987481B1Luminescence imaging with refining loop based on combination of partial illuminations
Publication Date: 2025.09.17 SURGVISION GMBH
  • EP3987481B1 patent drawingFigure 1
  • EP3987481B1 patent drawingFigure 2A
  • EP3987481B1 patent drawingFigure 2B

AI summary

A solution is proposed for imaging an object containing a luminescence substance. A corresponding method (500) is based on a refining loop. At each iteration of the refining loop, different spatial patterns are determined (516-518, 524;536-540, 546), partial illuminations corresponding to the spatial patterns are applied to the object (520,526;542,548), component images are acquired in response to the partial illuminations (522,528;544,550) and the component images are combined (530;552) into a combined image. A corresponding system (100) is also proposed. Moreover, a computer program (400) and a corresponding computer program product are proposed. A diagnostic method, a surgical method and a therapeutic method based on the same solution are further proposed.