Coronary Image Stabilization via Cardiac Phase Segmentation
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Solution Overview
Problem
Current medical imaging technologies face challenges in providing real-time, accurate image stabilization and tool actuation during coronary angioplasty procedures, particularly in synchronizing medical tools with the cyclical motion of moving organs, which affects the precision and effectiveness of interventions.
Innovation Solution
The development of a method and apparatus for generating a road map of blood vessels, stabilizing images, and actuating tools in synchronization with the cyclical motion of organs, using image processing techniques to derive and overlay edge lines, enhance vessel visibility, and synchronize tool deployment with specific phases of the organ's motion cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time image stabilization is implemented during coronary angioplasty procedures, then image accuracy is improved, but system complexity increases
Solution Approach 1:
The image stabilization process is divided into discrete phases corresponding to the cardiac cycle (e.g., systole, diastole). Images are selectively processed and stabilized based on the detected phase, rather than attempting to stabilize all images uniformly. This segmentation allows the system to manage complexity by processing only relevant frames at specific moments in the cardiac cycle.
Solution Approach 2:
The system performs preliminary detection of the cardiac phase using ECG signals or other motion detection methods before processing the images. By anticipating which images require stabilization based on the phase detection, the system can prepare and process images in advance, improving accuracy without requiring continuous complex processing of all images.
2Reliability
If tool actuation is synchronized with cyclical organ motion, then intervention effectiveness is improved, but timing precision requirements increase
Solution Approach 1:
The system utilizes the periodic nature of the cardiac cycle to synchronize tool actuation with specific phases (e.g., deploying a stent during systole when the coronary artery is most accessible). By leveraging the predictable periodicity of heartbeats, the system can achieve reliable synchronization without requiring extremely precise real-time timing adjustments for each individual action.
Solution Approach 2:
The system continuously monitors the cardiac phase through ECG signals or motion detection and uses this feedback to automatically trigger tool actuation at the optimal moment. This closed-loop feedback mechanism ensures that timing precision is maintained by continuously adapting to the actual cardiac rhythm, improving intervention effectiveness while managing the precision requirements through active adjustment rather than relying solely on pre-programmed timing.
3Measurement precision
If image processing is performed in real-time during procedures, then diagnostic accuracy is improved, but processing time increases
Solution Approach 1:
Instead of processing all images uniformly, the system applies image processing only to specific local regions or frames that correspond to critical phases of the cardiac cycle or contain areas of interest (such as the coronary arteries during systole). This selective processing maintains diagnostic accuracy for the most important images while significantly reducing the overall processing time by skipping less critical frames.
Solution Approach 2:
The system performs partial image processing focused on the most critical aspects (e.g., enhancing only the vascular structures during systole) rather than complete processing of all images. This partial action approach provides sufficient diagnostic accuracy for the key moments in the procedure while reducing processing time by avoiding unnecessary processing of less informative frames.
Data Source
AI summary
Apparatus and methods are described for imaging a portion of a body of a subject that undergoes motion. A plurality of image frames of the portion are acquired. A stream of image frames is generated in which a vicinity of a given feature of the image frames is enhanced, by (a) automatically identifying the given feature in each of the image frames, (b) aligning the given feature in two or more of the image frames, (c) averaging sets of two or more of the aligned frames to generate a plurality of averaged image frames, and (d) displaying as a stream of image frames the plurality of averaged image frames. Other embodiments are also described.