Skin Collagen Thickness Measurement Using 3D Surface Normalization
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Solution Overview
Problem
Current methods for measuring skin collagen thickness are limited by the need for strict calibration procedures, which restrict their application to small areas of skin with flat surface geometry, making it difficult to accurately measure collagen thickness over larger areas or those with non-flat geometries like the face.
Innovation Solution
An apparatus and method that use a digital camera, lighting calibration data, and 3D surface modeling to normalize light intensity variations due to surface geometry, allowing for the measurement of collagen thickness by processing infra-red and color channel data to account for illumination and orientation changes, enabling collagen thickness measurement over wider areas with non-flat surfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If strict calibration procedures are used to measure collagen thickness, then measurement precision is improved, but the method is limited to small areas with flat surface geometry
Solution Approach 1:
The patent changes the measurement parameter from absolute light intensity to light intensity ratios. By using ratios of light intensity at different wavelengths or positions, the method eliminates the need for strict calibration while maintaining measurement accuracy. This parameter transformation allows the system to work on various skin areas with different geometries without requiring flat surfaces or precise calibration procedures.
2Measurement precision
If calibration procedures are implemented, then measurement accuracy is improved, but device complexity and operational difficulty increase
Solution Approach 1:
The patent extracts and removes the calibration procedure from the measurement system. By using ratio-based measurements, the method eliminates the need for separate calibration steps and calibration references. This extraction simplifies the overall system operation, making it easier to use while maintaining measurement accuracy across different skin areas and geometries.
3Measurement precision
If calibration is performed on small flat areas, then measurement precision is improved, but the measurable area size is limited
Solution Approach 1:
The patent applies segmentation by measuring collagen thickness at multiple discrete points across the skin surface and then integrating or averaging these measurements. This allows the system to measure large areas by combining data from multiple smaller measurement points, maintaining precision while expanding the measurable area beyond the limitations of single-point calibration methods.
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 accurate measurement of skin collagen thickness over larger areas, including the face, by normalizing light intensity variations, thus overcoming the limitations of previous techniques and providing a more comprehensive analysis of skin histology.
Implementation Method 1
a digital camera to obtain image data of an area of skin when the area of skin is illuminated by light
Implementation Method 2
the Kubelka-Munk theory is sufficient to model light transport within skin
Implementation Method 3
a model of the scattering and absorption characteristics of the skin
Data Source
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AI summary
A camera (1) is provided which is operable to obtain a RGB and infra-red image of an area of illuminated skin (2). The obtained image is then passed to a computer (8) which determines the manner in which light returned by points on the surface of the illuminated area of skin (2) appearing in the obtained image varies due to variations in lighting intensity and surface geometry. The infra-red channel of the obtained image is then normalized on the basis of the determined variations and a measurement of collagen thickness can then be determined utilizing the processed infra-red channel of the obtained image. The determination of variations in intensities of light returned by points on the surface of the illuminated area of skin (2) can be achieved by processing an obtained image to generate a 3-D model of the surface being imaged and using the 3-D model to select and process pre-stored lighting level data.