3D Imaging Data Display Algorithms for Motion Artifact Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 3D minimally invasive imaging technologies face challenges in accurately imaging moving structures like a beating heart due to motion artifacts, requiring high refresh rates and motion compensation algorithms like ECG gating to maintain geometric accuracy and image quality.
Innovation Solution
The methods involve displaying subsets of 3D imaging data collected along frequently scanned dimensions, using texture maps to make obstructed structures transparent, and updating reconstructions dynamically to maintain temporal resolution and accuracy, while also localizing and orienting imaging probes within the 3D volume.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If mechanical scanning mechanisms are used to collect 3D imaging data, then the field of view is enlarged, but motion artifacts increase when imaging moving structures
Solution Approach 1:
The patent divides the 3D imaging data into multiple 2D cross-sectional slices that can be independently processed and displayed. This segmentation allows the system to handle large volumetric datasets more efficiently and reduces the impact of motion artifacts on the overall image quality by allowing selective processing of less affected slices.
Solution Approach 2:
The patent implements dynamic update mechanisms where the 3D reconstruction is continuously updated as new imaging data becomes available. The system dynamically adjusts the reconstruction based on the latest data while maintaining temporal resolution, allowing it to track moving structures more effectively and reduce motion artifacts through real-time adaptation.
2Measurement precision
If high refresh rates are used to image moving structures, then motion artifacts are reduced, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent extracts and displays only the most relevant 2D cross-sectional slices from the complete 3D volumetric data at each time point. By selectively presenting a subset of slices rather than processing and displaying the entire volume, the system maintains high temporal resolution for moving structures while significantly reducing the computational burden and device complexity.
Solution Approach 2:
The patent processes and displays a partial subset of the available imaging data (specific 2D slices) rather than the complete dataset. This partial action approach maintains the necessary temporal resolution for capturing moving structures while avoiding the excessive processing requirements that would result from processing the entire 3D volume at every refresh cycle.
3Loss of information
If complete 3D volumetric data is processed and displayed, then comprehensive anatomical information is provided, but the image processing time increases
Solution Approach 1:
The patent segments the complete 3D volumetric data into multiple 2D cross-sectional slices that can be processed and displayed independently. This segmentation enables the system to provide comprehensive anatomical information through the collection of slices while significantly reducing the processing time required compared to handling the complete volume as a single dataset.
Solution Approach 2:
The patent transforms the 3D volumetric data into a series of 2D cross-sectional slices, effectively reducing the dimensionality of the processing task. This dimensionality change allows comprehensive anatomical information to be preserved across multiple slices while the processing time is reduced by working with lower-dimensional data structures that can be handled more efficiently.
Data Source
AI summary
The present disclosure provides methods to process and/or display data collected using 3D imaging probes. The methods include: a) methods for mapping a single 2D frame onto a 3D representation of a volume; b) methods for dynamically updating portions of a 3D representation of a volume with a high temporal resolution, while leaving the remainder of the volume for contextual reference; c) methods for registering volumetric datasets acquired with high temporal resolution with volumetric datasets acquired with relatively low temporal resolution in order to estimate relative displacement between the datasets; and d) methods for identifying structures within a volume and applying visual cues to the structures in subsequent volumes containing the structures.