Optical Tomography Image Reconstruction Using Green Functions
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Solution Overview
Problem
Current methods for reconstructing the distribution of fluorophores in inhomogeneous objects with complex shapes are cumbersome, often requiring numerical methods and the use of a liquid index, which complicates the process and increases calculation time.
Innovation Solution
The method involves associating the second spatial coordinate of Green's functions with points on the object's second face and/or the first spatial coordinate with points on the first face, allowing for the determination of relevant Green functions without complex numerical methods or a liquid index, by bringing the object into contact with detectors or sources and zeroing signals from complementary parts to focus on contact-based measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If numerical methods are used to determine Green's functions for objects of any shape, then the accuracy of fluorophore distribution reconstruction is improved, but the calculation time and device complexity increase
Solution Approach 1:
The method segments the Green's function calculation by associating specific spatial coordinates with detector positions rather than calculating for all possible object shapes. This allows pre-computation of Green's functions for standard geometries, reducing calculation time while maintaining accuracy for fluorophore distribution reconstruction.
Solution Approach 2:
The patent performs preliminary determination of Green's functions for standard geometries before actual fluorophore distribution reconstruction. By pre-calculating and storing these functions, the method avoids time-consuming numerical computations during the reconstruction process itself, thereby reducing calculation time while preserving accuracy.
2Measurement precision
If numerical methods are used to determine Green's functions for objects of any shape, then the accuracy of fluorophore distribution reconstruction is improved, but the device complexity increases
Solution Approach 1:
The method divides the problem into two parts: determining Green's functions for standard geometries (simpler task) and using these functions for fluorophore distribution reconstruction (application task). This segmentation reduces device complexity by avoiding the need for complex numerical computation hardware while maintaining reconstruction accuracy.
Solution Approach 2:
The patent uses analytical solutions for standard geometries as substitutes for complex numerical methods. By copying and adapting Green's functions from known geometries, the method avoids the need for complex computational devices while achieving accurate fluorophore distribution reconstruction.
3Ease of operation
If a liquid index is used to simplify the reconstruction process, then the ease of operation is improved, but the device complexity and procedural complexity increase
Solution Approach 1:
The method extracts and eliminates the need for liquid index from the reconstruction process. By directly determining Green's functions for the object geometry without requiring immersion in liquid index, the patent simplifies the overall system while maintaining ease of operation for fluorophore distribution reconstruction.
4Adaptability or versatility
If Green's functions are determined for all possible object shapes, then the adaptability is improved, but the loss of time and computational resources increase
Solution Approach 1:
The patent creates a universal method that works for any object shape by determining Green's functions for standard geometries that can be applied to various object configurations. This universal approach maintains adaptability while avoiding the need to pre-calculate Green's functions for every possible shape, thereby reducing calculation time.
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
This approach simplifies the reconstruction of fluorophore distribution in objects of any shape without requiring a liquid index or complex numerical calculations, enabling faster and more accurate reconstruction of fluorophore distribution and optical parameters.
Implementation Method 1
illumination of the first face of the object with an excitation light of the fluorophores and the detection via a matrix of detectors of a light emitted by the second face of the object
Implementation Method 2
The problem is notably solved from the diffusion equation, established from the radiative transfer equation. Each source S generates in the medium a diffusive wave having the wavelength λex.
Data Source
AI summary
The method makes it possible to examine an inhomogeneous object (1) containing fluorophores (4) and having a first face (2) and an opposed second face (3). The first face (2) of the object (1) is illuminated with light for exciting the fluorophores (4). The light emitted by the second face (3) of the object (1) is detected by means of a matrix of detectors (D). The distribution of the fluorophores (4) is determined by means of pertinent Green functions each associated with first (C1) and second (C2) spatial coordinates. The second spatial coordinate (C2) of each of the pertinent Green functions corresponds to a point on the second face (3) of the object (1) and/or the first spatial coordinate (C1) of each of the pertinent Green functions corresponds to a point on the first face (2) of the object (1).