Target Vessel Reconstruction With Non-Rigid Motion Compensation
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Solution Overview
Problem
Existing motion compensation algorithms for 3D reconstruction of blood vessels fail to accurately compensate for non-rigid motion artifacts, particularly in small vascular structures, leading to blurring or poor compensation of soft tissue regions.
Innovation Solution
A method involving identification and erasure of secondary vessels in forward projection images, followed by automatic motion compensation to generate a secondary 3D reconstruction focused on the target vessel, using techniques like inpainting and consistency-based erasure to minimize secondary vessel influence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If general motion compensation algorithms are applied to 3D reconstruction, then reconstruction is achieved, but motion artifacts remain in small vascular structures and soft tissue regions
Solution Approach 1:
The patent segments the 3D volume into different tissue types (bone, soft tissue, vessels) and applies separate motion compensation optimization to each segment. This allows the algorithm to handle different motion characteristics of different tissues simultaneously, improving vessel reconstruction accuracy while reducing motion artifacts in soft tissue regions.
Solution Approach 2:
The patent applies local quality by using different optimization criteria for different anatomical regions within the same reconstruction. Specifically, it optimizes for vessel sharpness in vascular regions while allowing different optimization for soft tissue regions, thereby reducing motion artifacts locally where they most affect diagnostic quality.
2Reliability
If optimization concentrates on osseous structures, then bone regions are well-compensated, but soft tissue vessels become blurred
Solution Approach 1:
The patent divides the optimization process into separate segments for bone and soft tissue regions. By identifying and segmenting soft tissue regions containing vessels, the algorithm can apply vessel-optimized motion compensation specifically to these regions without compromising bone structure compensation, thereby maintaining reliability for both.
Solution Approach 2:
The patent implements local quality by applying different optimization weights and criteria to different anatomical regions. Soft tissue regions containing vessels receive optimized motion compensation that prioritizes vessel sharpness, while bone regions maintain their own optimization criteria, resolving the contradiction between bone compensation reliability and soft tissue vessel sharpness.
3Measurement precision
If multi-parameter optimization is applied to complex 3D fields, then comprehensive compensation is achieved, but algorithm complexity increases significantly
Solution Approach 1:
The patent reduces algorithm complexity by segmenting the 3D volume into distinct tissue regions and applying separate, simpler optimization algorithms to each segment. This avoids the need for a single complex multi-parameter optimization algorithm, thereby maintaining measurement precision while reducing device complexity.
Solution Approach 2:
The patent applies local quality by using different optimization strategies for different regions. Instead of applying a single complex optimization algorithm uniformly across the entire 3D field, it uses region-specific optimization that is computationally simpler and better suited to local characteristics, thereby reducing overall algorithm complexity while maintaining compensation accuracy.
Data Source
AI summary
A method for motion-compensated reconstruction of a target vessel by providing a primary 3D reconstruction of a volume including the target vessel, identifying an image of the target vessel and an image of a secondary vessel different from the target vessel in the primary 3D reconstruction, forward-projecting the image of the target vessel and the image of the secondary vessel onto forward projection images, erasing the image of the secondary vessel in the forward projection images, and generating a secondary 3D reconstruction from the forward projection images with automatic motion compensation.