3D Body Surface Mapping for Longitudinal Thermal Image Alignment
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Solution Overview
Problem
Thermal imaging systems face challenges in accurately aligning and comparing images of a human body target area over time due to limited resolution and difficulty in mapping images to anatomical body parts, especially when the patient's shape changes or moves, complicating the identification of the same target area in different images.
Innovation Solution
A computer-implemented method and system that uses a statistical shape model (SSM) to generate a 3D model of the human body surface, aligning multiple images by mapping them onto this model, incorporating physical data and warping to account for body deformations, and utilizing multiple cameras (infrared, UV, and visual light) for precise anatomical alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If thermal imaging is used to monitor body conditions over time, then detection of lesions and abnormal conditions is enabled, but image alignment and anatomical identification become difficult due to limited resolution and body shape changes
Solution Approach 1:
The patent introduces a statistical shape model (SSM) as an intermediary framework that mediates between thermal images and anatomical structures. The SSM serves as a common reference space that allows accurate mapping and alignment of thermal images to anatomical locations, resolving the alignment precision problem while maintaining detection reliability.
Solution Approach 2:
The patent transitions from two-dimensional thermal images to three-dimensional anatomical models by incorporating depth information and spatial coordinates. This dimensional transformation enables precise localization of thermal features onto anatomical structures, overcoming the limited resolution and alignment difficulties in 2D space.
2Duration of action of moving object
If images are taken at different time points to monitor changes, then temporal monitoring is enabled, but mapping images to anatomical areas becomes more difficult due to weight changes and shape variations
Solution Approach 1:
The patent employs statistical shape models that can adapt to parameter changes in body shape and size over time. The SSM framework allows the same anatomical reference system to accommodate variations in body morphology across different time points, maintaining precise anatomical mapping while enabling long-term monitoring.
Solution Approach 2:
The patent establishes a statistical shape model framework in advance that can accommodate future variations in body shape. By pre-defining the anatomical reference space and its transformations, the system is prepared to accurately map images from different time points without requiring re-calibration when body changes occur.
3Device complexity
If a single 2D imaging camera is used, then device simplicity is maintained, but identification of target area in moving body becomes difficult
Solution Approach 1:
The patent replaces the mechanical approach of using multiple physical cameras with a computational geometry-based solution. By using statistical shape models and 3D transformation algorithms, the system achieves precise target area identification through software processing of single 2D images, eliminating the need for complex multi-camera hardware while maintaining high identification precision.
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 monitoring of a human body target area over time, allowing for precise comparison and tracking of conditions such as inflammation or overload, even with low-resolution images, by ensuring anatomical alignment and adjusting for body movement and shape changes.
Implementation Method 1
Thermal imaging of a human body is configured to record thermal radiation of the human body
Implementation Method 2
warping to account for body deformations
Data Source
AI summary
A method and a system for processing a plurality of camera images of a human body surface target area over time includes the steps of obtaining a plurality of images of a human body surface target area of a human body captured by a first camera over time, obtaining physical data of the human body, and generating a 3D model of at least the human body surface target area.