Electromagnetic Interference Pattern Recognition Tomography for Brain Imaging
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Solution Overview
Problem
Existing electromagnetic tomography (EMT) methods struggle to accurately image objects with high dielectric contrast shields, such as the human brain, due to the complexity of diffraction tomography and the amplification of electromagnetic interference patterns.
Innovation Solution
The method involves generating an electromagnetic interference picture within an imaging domain, recognizing and nullifying or diminishing the interference patterns, and revealing the 3D dielectric structure of the object through a recursive process of forming undisturbed and disturbed interference images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electromagnetic tomography is used to image objects with high dielectric contrast shields, then the ability to image deep brain tissues is improved, but electromagnetic interference patterns cause amplified distortions and reduce measurement precision
Solution Approach 1:
The patent applies preliminary action by performing pattern recognition and nullification on electromagnetic interference patterns before they can distort the final image reconstruction. The system identifies characteristic interference patterns in the measured data and removes them through subtraction or division operations, preventing rather than correcting the distortion in the final brain tissue images
Solution Approach 2:
The patent converts the harmful electromagnetic interference patterns into a beneficial diagnostic tool by recognizing that these patterns contain information about the dielectric structure of tissues. The interference patterns, which were previously considered purely harmful distortions, are now used to enhance the imaging capability by providing additional information about tissue properties when properly processed
2Reliability
If diffraction tomography is applied to high dielectric contrast objects, then the ability to penetrate shields is improved, but the complexity of the tomography process increases and amplifies interference patterns
Solution Approach 1:
The patent extracts and separates the electromagnetic interference patterns from the useful signal containing information about brain tissue dielectric properties. By identifying and removing the interference components through pattern recognition algorithms, the system isolates the relevant diagnostic information from the complex measured data, simplifying the interpretation process
Solution Approach 2:
The patent applies dynamics by using iterative reconstruction algorithms that dynamically adjust the image reconstruction process based on the measured electromagnetic data. The system repeatedly refines the dielectric property distribution estimates, comparing predicted and actual measurements to progressively improve image accuracy while accounting for interference patterns
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 effectively reduces the distortion caused by electromagnetic interference patterns, allowing for the accurate reconstruction of the 3D dielectric structure of objects with high dielectric contrast shields, such as the human brain.
Implementation Method 1
via an electromagnetic tomography system, generating electromagnetic field data corresponding to an object in an imaging domain, wherein the electromagnetic field data is measured at a plurality of receivers after being produced at a plurality of transmitters
Implementation Method 2
an electromagnetic interference picture is generated within an imaging domain, revealing the superposition of 3D dielectric structure of an object together with electromagnetic interference pattern
Implementation Method 3
the complexity of diffraction tomography
Data Source
AI summary
An Electromagnetic Interference Pattern Recognition Tomography (EMIPRT) method for use in an image reconstruction system includes generating electromagnetic field data corresponding to an object in an imaging domain, via an electromagnetic tomography system, and using the generated electromagnetic field data, repeatedly, in recursive manner, forming an undisturbed electromagnetic interference image, forming a disturbed electromagnetic interference image based on the undisturbed electromagnetic interference image, recognizing electromagnetic interference patterns in the repeatedly formed disturbed electromagnetic interference images, and forming a superposition image by nullifying or diminishing the recognized electromagnetic interference patterns from the disturbed electromagnetic interference image. Forming a disturbed electromagnetic interference image is also based on an object factor that is a function of the differences between experimentally electromagnetic fields and electromagnetic fields calculated during the step of forming an undisturbed electromagnetic interference image. After each repeated step of forming a superposition image, the method also includes determining whether a convergence objective has been reached.