Cancer Identification via Gamma Photon Oscillation Analysis
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Solution Overview
Problem
Current cancer detection methods are costly, time-consuming, and prone to human error due to the need for manual analysis of images from multiple angles, which limits their accessibility and accuracy.
Innovation Solution
A cancer identifying device that uses radioactive tracers to emit gamma photons, which are converted into oscillating waves for analysis by an AI platform, allowing for accurate identification of cancerous areas and types using a portable, cost-effective system that can be implemented on devices like smartphones or tablets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging techniques (CT, MRI, PET, ultrasound, mammography) are used for cancer detection, then detection capability is achieved, but cost increases and manual analysis time increases
Solution Approach 1:
The system enables automated cancer detection and classification through AI algorithms that automatically analyze gamma photon data without requiring manual intervention by radiologists or medical professionals, making the system self-sufficient in the detection process
Solution Approach 2:
The patent replaces manual mechanical analysis by medical professionals with an automated electronic system that detects gamma photons and uses AI algorithms to identify and classify cancer, substituting human cognitive processes with computational algorithms
2Measurement precision
If conventional imaging systems are used, then cancer detection is possible, but device complexity and hardware constraints increase
Solution Approach 1:
The patent extracts the essential detection function from complex conventional imaging systems by using only gamma photon detection with AI analysis, removing unnecessary imaging hardware and simplifying the system to core components: gamma photon detector, processor, and AI algorithms
Solution Approach 2:
The system is designed to be platform-agnostic and can be implemented on various devices including smartphones, tablets, or dedicated medical devices, making it universally deployable across different hardware configurations without being constrained to specific complex imaging systems
3Reliability
If multiple-angle imaging is performed, then comprehensive cancer detection is achieved, but productivity decreases
Solution Approach 1:
The system uses radioactive tracers that are administered beforehand to the patient, which accumulate in cancer cells and emit gamma photons. This preliminary action enables direct detection of cancer metabolic activity without requiring multiple imaging angles or repeated scans
Solution Approach 2:
The patent introduces radioactive tracers as an intermediary substance that selectively accumulates in cancer cells and emits gamma photons, serving as a mediator that directly reveals cancer locations and types through metabolic activity rather than requiring complex multi-angle structural imaging
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 provides rapid, accurate, and cost-effective cancer detection with minimal human error, enabling efficient identification and tracking of cancer growth, and can be used by non-experts, without the need for multiple-angle imaging.
Implementation Method 1
uses radioactive tracers to emit gamma photons
Implementation Method 2
gamma photons are converted into oscillating waves
Data Source
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AI summary
A method and device for identifying cancer is disclosed. The method includes receiving gamma photons emitted from cancer cells present in an organism through at least one photoreceptor cell. The method further includes converting the gamma photons received through the at least one photoreceptor cell to a plurality of oscillating waves having a plurality of frequencies. The method includes creating a contour plot by projecting positive and negative peaks of each of the plurality of oscillating waves. The method further includes comparing pattern of the contour plot with a plurality of training contour plots to identify type of cancer affecting at least one body part of the organism, wherein each of the plurality of training contour plots are tagged with an associated type of cancer.