Multi-Image Registration for Accurate 3D Surface Reconstruction
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Solution Overview
Problem
Medical imaging systems face challenges in accurately displaying the size of objects within a three-dimensional scene due to fixed pixel size and varying distances from the collection optic, leading to inconsistent object sizing and complexity in registering and reconstructing multiple images during procedures like lithotripsy.
Innovation Solution
A method involving image processing algorithms that utilize feature distance maps and positional changes of a digital camera to generate a three-dimensional surface approximation by selecting pixels based on proximity to central axes and incorporating illumination data to enhance registration and reconstruction, minimizing computational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are captured from different positions to enable three-dimensional reconstruction, then the accuracy of size estimation is improved, but the computational complexity increases
Solution Approach 1:
The patent segments the image processing task by identifying and extracting only the necessary features (distance maps, central axes, unique scene features) from multiple images, rather than processing entire images. This segmentation allows three-dimensional reconstruction while reducing computational complexity by focusing only on critical data elements.
Solution Approach 2:
The patent extracts essential information from multiple images including distance maps, central axes, and unique scene features. By taking out only the necessary components for three-dimensional reconstruction rather than processing complete images, the system achieves accurate size estimation while minimizing computational requirements.
2Measurement precision
If image registration and reconstruction algorithms are applied to enhance clarity and accuracy, then the quality of visual field is improved, but the processing time increases
Solution Approach 1:
The patent performs preliminary actions by pre-identifying unique features, generating distance maps, and establishing central axes before the actual registration and reconstruction processes. This preliminary preparation organizes data in advance, enabling faster processing during the actual reconstruction phase while maintaining high accuracy.
Solution Approach 2:
The patent replaces traditional mechanical image processing methods with algorithmic approaches that use mathematical models for feature detection, distance calculation, and three-dimensional reconstruction. This substitution enables efficient processing with reduced time requirements while achieving superior accuracy compared to conventional methods.
3Measurement precision
If feature distance maps and positional changes are utilized for reconstruction, then the accuracy of three-dimensional representation is improved, but the device complexity increases
Solution Approach 1:
The patent introduces distance maps as an intermediary element that bridges the gap between two-dimensional images and three-dimensional reconstruction. By using distance maps as a mediator that encodes spatial information, the system achieves accurate three-dimensional representation without requiring complex direct reconstruction algorithms, thereby managing algorithmic complexity.
Data Source
AI summary
Systems and methods related to combing multiple images are disclosed. An example method of combining multiple images of a body structure includes capturing a first input image with a digital camera positioned at a first location at a first time point, representing the first image with a first plurality of pixels, capturing a second input image with the digital camera positioned at a second location at a second time point, representing the second image with a second plurality of pixels, generating a first feature distance map of the first input image, generating a second feature distance map of the second input image, calculating the positional change of the digital camera between the first time point and the second time point and utilizing the first feature distance map, the second feature distance map and the positional change of the digital camera to generate a three-dimensional surface approximation the body structure.