Breast Image Alignment via Shape Analysis and Robust Point Matching
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Solution Overview
Problem
Conventional methods for aligning breast images, such as nipple or pectoralis alignment, are suboptimal due to variability in breast position and challenges in accurate nipple detection, leading to a need for more robust alignment techniques to facilitate effective image analysis.
Innovation Solution
A method utilizing shape information to align breast images by segmenting them into direct exposure and foreground regions, determining the skin boundary, and applying the Robust Point Matching technique for precise alignment of relevant parts, allowing for optimal placement of similar structures at the same height.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If nipple alignment is used for aligning breast images, then the alignment process is simple, but the alignment accuracy deteriorates due to variability in breast position and challenges in accurate nipple detection
Solution Approach 1:
The patent extracts and removes the problematic nipple detection step from the alignment process. Instead of relying on nipple detection, the method uses automatic alignment based on breast tissue density patterns and image processing algorithms that directly compute optimal alignment without requiring manual or automated nipple identification, thereby eliminating the source of alignment errors while maintaining simplicity
Solution Approach 2:
The patent replaces the manual/mechanical nipple alignment process with an automated image processing system that uses computational algorithms to analyze breast tissue density patterns, grayscale variations, and anatomical structures. This substitution of mechanical alignment with computational image analysis achieves both automation and high precision simultaneously
2Stability of the object's composition
If pectoralis alignment is used for aligning breast images, then the alignment may be more stable, but it becomes suboptimal when breast position during acquisition varies
Solution Approach 1:
The patent implements a dynamic alignment system that automatically adapts to different breast positions and anatomical variations. The algorithm processes each image pair independently, computing optimal alignment parameters based on the actual tissue density patterns present in each image, rather than relying on fixed anatomical landmarks. This dynamic computation ensures both stability and adaptability across varying acquisition conditions
Solution Approach 2:
The patent changes the alignment parameters from fixed anatomical landmark coordinates (nipple or pectoralis position) to dynamic parameters derived from image processing, including tissue density gradients, grayscale distribution patterns, and automated feature detection. These parameter changes enable the system to adapt to position variations while maintaining consistent alignment quality
3Ease of operation
If alignment based on key features (nipple or pectoralis) is used, then the alignment process is straightforward, but the alignment quality deteriorates because it does not account for overall breast structure similarity
Solution Approach 1:
The patent creates a universal alignment method that simultaneously considers multiple aspects of breast structure including tissue density patterns, overall shape, grayscale distribution, and anatomical features. Rather than relying on a single key feature, the system integrates multiple image characteristics into a comprehensive alignment algorithm that achieves both simplicity and high quality through multi-functional image analysis
Data Source
AI summary
A method of aligning at least two breast images includes aligning a relevant image part in each of the images, the relevant image parts being obtained on the basis of the result of a shape analysis procedure performed on the breast images.