Diffusion Optical Tomography System for Real-Time Imaging
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Solution Overview
Problem
Current diffusion optical tomography techniques require large matrix operations for high image resolution, leading to long imaging times and bulky systems, making real-time scanning and imaging impractical, especially for home use.
Innovation Solution
A device and method incorporating a sensing circuit with light sources and sensors, a control unit, computation unit, and image reconstruction unit on a flexible printed circuit and system-on-chip, enabling real-time image processing and miniaturization for portable use by setting optical parameters, constructing image models, and reconstructing images using near-infrared light.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large matrix operations are performed for high image resolution, then image resolution is improved, but imaging time increases and device size becomes bulky
Solution Approach 1:
The patent segments the image reconstruction process into multiple stages: data acquisition, preprocessing, iterative reconstruction algorithm execution, and final image generation. By dividing the computation into manageable segments that can be processed sequentially or parallelly, the system achieves high resolution without requiring all matrix operations to complete simultaneously, thus reducing overall imaging time.
Solution Approach 2:
The patent performs preliminary actions by pre-calculating system matrices, pre-processing optical data, and initializing reconstruction parameters before actual image reconstruction. This preparation work reduces the computational burden during real-time imaging, allowing high resolution to be achieved with shorter imaging times.
2Measurement precision
If large matrix operations are performed for high image resolution, then image resolution is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical computing systems with optimized algorithms and software-based matrix operations. By using efficient reconstruction algorithms (such as iterative methods, compressed sensing, or machine learning-based approaches) instead of traditional mechanical or hardware-based matrix processors, the system achieves high resolution imaging with a more compact and less complex device structure.
Solution Approach 2:
The patent changes key parameters of the reconstruction process, such as adjusting matrix size, optimization criteria, convergence thresholds, or using dimensionality reduction techniques. These parameter changes allow the system to maintain high image resolution while reducing the computational complexity and physical size of the device by working with optimized, smaller-scale representations of the imaging data.
3Productivity
If real-time imaging is implemented, then imaging speed is improved, but computational requirements increase device complexity
Solution Approach 1:
The patent implements periodic action by using iterative reconstruction algorithms that update the image solution in repeated cycles. Each iteration refines the image quality, and the process continues until convergence or a predetermined number of iterations is reached. This periodic computational approach enables real-time imaging by breaking down the complex reconstruction task into manageable periodic steps that can be executed quickly.
Solution Approach 2:
The patent maintains continuity of useful action by implementing real-time data acquisition and continuous image reconstruction processes. The system continuously acquires optical data, processes it through the reconstruction algorithm, and generates updated images without interruption. This continuous operation, enabled by optimized computational methods, achieves real-time imaging performance without requiring overly complex hardware systems.
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
Enables real-time image processing and device miniaturization, allowing for portable diffusion optical tomography that can be used on the body, facilitating real-time imaging and reducing costs, making it suitable for home care and various medical applications.
Implementation Method 1
Oxygenated and non-oxygenated hemoglobin have different levels of absorption to near-infrared light
Implementation Method 2
diffusion optical tomography technology often uses near-infrared light in clinic trials
Data Source
AI summary
A device and method for diffusion optical tomography are disclosed. The device includes a sensing circuit with a plurality of light sources and sensors and an optical tomography element having a control unit, a computation unit and an image reconstruction unit. First, the computation unit constructs an image model of an object using optical parameters of the object, and performs decomposition on the image model. Then, the control unit instructs the light sources to emit light to the object, and receives a plurality of optical signals generated by the object in response to the light. Finally, the image reconstruction unit combines the optical signals and the decomposed image model and reconstructs an image of the object based on the combination of the optical signals and the decomposed image model.