DOT Image Reconstruction Using Structural Prior Initial States
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Solution Overview
Problem
Diffuse Optical Tomography (DOT) faces challenges in accurately obtaining actual optical coefficients due to its complex nonlinear and ill-posed inverse reconstruction characteristics, leading to difficulties in body imaging and reduced image quality and accuracy.
Innovation Solution
An image reconstruction method that uses a structural image to determine an inhomogeneous initial state, allowing for iterative calculations between forward and inverse reconstructions, enabling more precise and rapid image reconstruction without requiring a homogeneous state, and employing a diffusion optical model to refine optical coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If homogeneous optical coefficient is used in forward computing, then the calculation is simplified, but the image reconstruction accuracy deteriorates
Solution Approach 1:
The patent applies preliminary action by using structural images (from MRI, CT, or mammography) to pre-determine the initial optical coefficient distribution before iterative reconstruction. This preliminary step provides a more accurate starting point that reflects actual tissue heterogeneity, reducing the number of iterations needed and improving final accuracy without significantly increasing computational complexity
Solution Approach 2:
The patent implements local quality by transitioning from a uniform homogeneous optical coefficient model to a spatially varying inhomogeneous model derived from structural images. Different regions of the tissue are assigned different optical coefficients based on their structural characteristics, allowing the model to capture local tissue heterogeneity while maintaining computational feasibility through iterative refinement
2Productivity
If iterative reconstruction is performed with homogeneous initial state, then the computation is faster, but the spatial resolution deteriorates
Solution Approach 1:
The patent uses structural images to pre-establish the spatial distribution pattern of optical coefficients before iterative reconstruction begins. This preliminary spatial mapping preserves anatomical boundaries and tissue heterogeneity information, allowing the iterative process to converge faster to a high-resolution solution rather than starting from a uniform homogeneous state
Solution Approach 2:
The patent changes the initial state parameter from homogeneous to inhomogeneous by incorporating structural image information. This parameter change provides the iterative algorithm with a more realistic starting distribution that accelerates convergence while maintaining spatial resolution, as the algorithm needs fewer iterations to refine already-accurate regional variations
3Measurement precision
If inhomogeneous initial state is used based on structural image, then the image reconstruction accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent applies universality by using multi-functional structural images (from MRI, CT, or mammography systems) that serve dual purposes: their primary diagnostic function and their secondary function as the basis for determining optical coefficient distributions in DOT reconstruction. This multi-functionality approach leverages already-acquired imaging data, avoiding the need for additional specialized imaging equipment while improving reconstruction accuracy
Solution Approach 2:
The patent introduces a computational intermediary that processes structural images to generate optical coefficient maps. This intermediary software module acts as a bridge between the structural imaging data and the DOT reconstruction algorithm, translating anatomical information into optical properties without requiring additional physical hardware, thereby managing system complexity through software-based integration
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 method enhances spatial resolution and accuracy in body imaging by iteratively converging theoretical and actual optical detected results, improving image quality and speed of reconstruction.
Implementation Method 1
a homogeneous optical coefficient provided by a diffuse optical model
Implementation Method 2
emitting an incident light into the object by a light source, and detecting a luminous intensity of diffusion light passing through the object
Data Source
AI summary
An image reconstruction method is described as follows. A structural image of an object is obtained. An actual optical detected result of the object is obtained. An inhomogeneous initial state is determined based on the structural image. At least one solution converged with the actual optical detected result is determined by iteratively calculating a physical model from the inhomogeneous initial state. The image of the object is reconstructed based on the solution.