Fiducial Marker Tissue Image Normalization
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Solution Overview
Problem
Conventional clinical imaging methods lack control over light sources, exposure, and optical characteristics, making it difficult to accurately correlate and rectify images of skin tissue over time, especially due to variations in ambient conditions and complex interactions of light with tissue layers.
Innovation Solution
A system and method that utilize fiducial markers with well-defined shapes and color variations, including optical phantoms to simulate the spectral character of skin, allowing for correction and analysis of digital images in three dimensions by cross-referencing spatial and spectral components, and generating a three-dimensional digital reconstruction of lesions using multispectral data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional clinical imaging methods are used without control over light source and exposure, then image acquisition is simple and quick, but image correlation and rectification accuracy deteriorates due to variations in ambient conditions and optical characteristics
Solution Approach 1:
A fiducial marker is introduced as an intermediary object in the imaging field of view to enable accurate image correlation and rectification. The marker contains multiple colored sections with known spectral characteristics that serve as reference points for comparing and correcting variations between images taken at different times and under different lighting conditions
Solution Approach 2:
The system captures images at multiple wavelengths (spectral imaging) to obtain information about tissue optical properties. By analyzing spectral signatures across different wavelengths, the system can distinguish between tissue types and track changes over time while compensating for variations in lighting and exposure conditions
2Measurement precision
If spectral imaging with multiple wavelengths is implemented, then tissue optical property analysis improves, but device complexity and data processing requirements increase
Solution Approach 1:
The system extracts and analyzes only the relevant spectral information from multi-wavelength images. By focusing on specific spectral signatures of tissue components (melanin, hemoglobin, water) and using the fiducial marker for reference, the system extracts meaningful data while filtering out redundant information, thereby managing complexity
3Measurement precision
If fiducial markers with optical phantoms are used to simulate skin spectral character, then spectral correction accuracy improves, but manufacturing complexity of the marker increases
Solution Approach 1:
The fiducial marker contains multiple colored sections, each with specific spectral characteristics that match or simulate the spectral properties of different skin components. This local differentiation of spectral properties within the marker enables comprehensive spectral correction while using standard manufacturing techniques for creating colored sections
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 clinicians to quickly acquire and analyze skin images by normalizing and correcting for spectral effects, allowing for automated diagnostic decisions and tracking of lesion growth, while establishing a baseline for individual patients, improving diagnostic accuracy and efficiency.
Implementation Method 1
optical phantoms to match the spectral character of living tissue
Implementation Method 2
have a reflective layer to simulate an optical character of living bodily tissue such as skin
Data Source
AI summary
In medical imaging, a fiducial marker facilitates tissue image correlation that allows for image analysis, normalization and correction of the optical exposure and spectral and spatial distribution in order to compensate for the surface reflections, sub surface tissue interactions and spatial orientation of the excitation and imaging axes to the subject tissue. Using a cross comparison, clinicians can model tissue image data in different forms in order to reference and compare data from various spectral components and or from different images. This may enhance human interpretation between images including the variations between images even when the spectral, spatial and optical conditions or the image resolution or sensitivity are compromised. Such may be used to assess cosmetic, moisturizing, therapeutic materials and treatments.