3D Pigmentation Disorder Profiling via Multi-Angle Imaging
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Solution Overview
Problem
Current methods for evaluating skin pigmentation disorders rely on two-dimensional imaging, which are limited in specificity and sensitivity, failing to incorporate essential three-dimensional parameters such as depth, volume, and surface roughness, making early identification of suspicious moles challenging.
Innovation Solution
A method and system that acquire 2D images from multiple angles, reconstruct 3D images, compute and evaluate parameters like asymmetry, border, color, diameter, volume, and thickness, and iteratively compare data over time to generate a dynamic profile of pigmentation disorders, creating a knowledge base for each individual.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If two-dimensional imaging techniques are used to evaluate pigmentation disorders, then the method is simple and widely applicable, but the specificity and sensitivity remain insufficient
Solution Approach 1:
The patent transitions from two-dimensional imaging to three-dimensional imaging by acquiring images from multiple angles and reconstructing volumetric data. This dimensional expansion enables measurement of depth, volume, and surface roughness parameters that are invisible in 2D, directly improving measurement precision for pigmentation disorder evaluation
2Measurement precision
If three-dimensional imaging is implemented to capture depth and volume parameters, then measurement precision improves, but device complexity and data processing requirements increase
Solution Approach 1:
The imaging system is designed to perform multiple functions: capturing 2D images from multiple angles, reconstructing 3D volumetric data, and extracting various parameters (depth, volume, surface roughness, ABCD criteria) from the same dataset. This multi-functionality reduces the need for separate specialized devices while achieving comprehensive measurement precision
3Reliability
If multiple parameters are computed and evaluated over multiple dates, then the dynamic profile and predictive analysis improve, but the data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing by organizing images and computing parameters at each acquisition date, storing intermediate results in structured folders. This preliminary action enables efficient comparison and aggregation in subsequent analyses, reducing the computational burden when generating dynamic profiles across multiple time points
4Measurement precision
If comprehensive parameter evaluation is performed for each pigmentation disorder, then diagnostic accuracy improves, but the complexity of data management and analysis increases
Solution Approach 1:
The data management system segments information into organized folders for each pigmentation disorder, separating images, computed parameters, and expert evaluations. This segmentation structure enables systematic handling of comprehensive parameters while maintaining data accessibility and reducing management complexity through modular organization
Data Source
AI summary
A method for characterizing cutaneous pigmentary disorders in an individual which includes: for each pigmentary disorder: on a date tkm acquiring 2D images of a pigmentary disorder from a plurality of angles and reconstructing at least one 3D image; storing the images in a first folder; on the basis of the images, calculating parameters of the pigmentary disorder, and storing in a second folder; evaluating the parameters and storing in a third folder; iterating at least one of the four preceding steps on multiple dates, and for each iteration: comparing the data for at least one period and identifying the changes; storing in a fourth folder per period; for each fourth folder, grouping the folders together in a fifth folder defining a snapshot of the pigmentary disorder; aggregating the fifth folders in a sixth folder defining a dynamic profile of the pigmentary disorder; iterating the preceding steps to obtain a sixth folder for each additional pigmentary disorder; and generating, for the individual, a knowledge base of their pigmentary disorders aggregating the sixth folders.