Breast Tomosynthesis Motion Detection via Pectoral Muscle Boundary Analysis
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Solution Overview
Problem
Existing breast tomosynthesis imaging procedures face challenges in detecting internal breast tissue motion during imaging, which can lead to blurred images, anatomical distortions, and the need for additional imaging sessions.
Innovation Solution
The method involves compressing the breast in a mediolateral oblique (MLO) position and acquiring multiple tomosynthesis MLO projection frames. By identifying and generating representations of the pectoral muscle boundary in these frames, the method calculates differences between these representations to determine motion and generates a motion score, which can trigger a motion warning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If breast tomosynthesis imaging is performed without motion detection, then the imaging procedure is simple and quick, but internal breast tissue motion causes blurred images and anatomical distortions
Solution Approach 1:
The system performs preliminary motion detection by analyzing boundary representations of the pectoral muscle across multiple projection frames before final image reconstruction. This preliminary action identifies motion artifacts early, allowing for corrective measures to be taken before committing to reconstructed images, thereby improving image quality without significantly increasing overall procedure complexity.
Solution Approach 2:
The patent introduces an intermediary motion detection mechanism that uses boundary representations of the pectoral muscle as a surrogate marker for internal tissue motion. Instead of directly measuring all tissue motion, the system uses the easily identifiable pectoral muscle boundary as an intermediary indicator, simplifying the detection process while maintaining reliability.
2Measurement precision
If motion detection is implemented during tomosynthesis imaging, then image quality and diagnostic accuracy improve, but the imaging procedure becomes more complex and time-consuming
Solution Approach 1:
The system extracts only the essential information needed for motion detection by focusing specifically on the boundary representations of the pectoral muscle in projection frames. Instead of analyzing all image data, the method isolates and processes only the relevant boundary features, achieving accurate motion detection while minimizing additional processing time.
Solution Approach 2:
The patent applies partial action by performing motion detection on a subset of projection frames rather than all frames. By selecting key frames for boundary analysis, the system achieves sufficient motion detection accuracy without the time cost of analyzing every single projection frame, thus balancing precision with time efficiency.
3Measurement precision
If multiple projection frames are acquired for motion analysis, then motion detection accuracy improves, but the imaging procedure complexity and data processing requirements increase
Solution Approach 1:
The patent segments the complex task of motion detection into manageable steps: acquiring multiple projection frames, extracting boundary representations of the pectoral muscle from each frame, comparing these representations across frames, and generating motion scores. This segmentation breaks down the complex data processing into systematic, manageable operations that improve precision without overwhelming system complexity.
Solution Approach 2:
The system applies local quality by focusing computational resources on specific regions of interest - the boundary areas of the pectoral muscle in each projection frame. Instead of processing entire images uniformly, the method concentrates analysis on the boundary regions where motion indicators are most prominent, improving detection precision while reducing overall data processing complexity.
Data Source
AI summary
Methods and systems for identifying internal motion of a breast of a patient during an imaging procedure. The method may include compressing the breast of the patient in a mediolateral oblique (MLO) position. During compression of the breast, a first tomosynthesis MLO projection frame for a first angle with respect the breast is acquired and a second tomosynthesis MLO projection frame for a second angle with respect to the breast is acquired. Boundaries of the pectoral muscle are identified in the projection frames and boundary representations are generated. A difference between the first representation and the second representation is determined. A motion score is then generated based on at least the difference between the first representation and the second representation.