3D Cardiovascular Model Frame Selection via Cardiac Cycle Sync
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Solution Overview
Problem
Current methods for building 3D models of the cardiovascular system require manual selection of 2D images from disjointed video streams captured at different times, leading to inefficiencies and potential errors in creating high-quality models.
Innovation Solution
An automated method that uses cardiac cycle data to select optimal frames from non-overlapping video streams captured by the same or different medical imaging devices, allowing for the construction of a 3D model based on synchronized cardiac cycle events, such as the end of diastole, to enhance image quality and reduce manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual selection of 2D images is performed to create 3D models from disjointed video streams, then compatibility of images for 3D modeling can be achieved, but time consumption and potential for human error increase
Solution Approach 1:
The system automatically performs frame selection by analyzing cardiac cycle data and video stream timestamps without requiring manual intervention. The computer identifies compatible frames based on temporal alignment with cardiac events, making the system self-sufficient in selecting appropriate images for 3D model construction.
Solution Approach 2:
The system uses cardiac cycle data as feedback to guide frame selection. By comparing timestamps of video frames with cardiac event timing, the system dynamically identifies frames that capture anatomical structures at corresponding phases of the cardiac cycle, ensuring compatibility across disjointed video streams.
2Ease of manufacture
If frames are selected from disjointed video streams without synchronization, then image acquisition is simplified, but manufacturing precision of the 3D model deteriorates
Solution Approach 1:
Cardiac cycle data serves as feedback to synchronize frame selection from disjointed video streams. The system compares frame timestamps with cardiac event timing to identify frames captured at corresponding physiological phases, ensuring anatomical consistency and 3D model accuracy despite temporal gaps between video acquisitions.
Solution Approach 2:
The patent replaces manual mechanical synchronization with automated computational analysis. Instead of physically coordinating video stream acquisition, the system uses algorithmic analysis of timestamps and cardiac cycle data to identify and select compatible frames, substituting mechanical coordination with information processing.
3Measurement precision
If additional imaging devices are used to capture overlapping video streams, then frame selection accuracy improves, but device complexity and cost increase
Solution Approach 1:
The system creates a temporal copy of cardiac cycle information by extracting timing data from existing video streams and cardiac annotations. Instead of acquiring separate synchronized video streams from multiple devices, the system copies and analyzes timestamp information from available streams alongside cardiac cycle data to achieve accurate frame selection.
Solution Approach 2:
The patent makes the imaging system multi-functional by enabling accurate 3D model construction from disjointed video streams using a single imaging device. The system performs both image acquisition and temporal synchronization functions through automated analysis of cardiac cycle data, eliminating the need for additional specialized imaging devices.
Data Source
AI summary
To create a 3D model of part of a cardiovascular system, two 2D images taken of different orientations of the cardiovascular system may be combined. The 2D images originate from video streams taken at different points in time, which comprise frames showing a beating heart, and thus a moving cardiovascular system. Because of this movement, not just any random set of two 2D images may result in useable 3D model. To select a proper set of two 2D images, a method is provided wherein said selection is based on cardiac cycle data. The cardiac cycle data may comprise heart activity data as a function of time and timing data on cycle events. These cycle events may be repetitive, as the same events occur with every heartbeat. The selected frames are preferably selected at, or approximately at, similar events.