4DCT Respiratory Phase Error Reduction via Waveform Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing 4DCT respiratory imaging methods suffer from phase error due to discrepancies between target and actual phases, leading to irregularity and temporal degradation of the 4D image series, which can be mitigated by increasing image sampling but at the cost of longer reconstruction times and larger datasets.
Innovation Solution
The method involves performing waveform analysis on cine scan data to identify exact timepoints for image generation, allowing for precise reconstruction of images centered at specified phases, eliminating phase error and enabling flexible image generation based on any trigger points in the respiratory signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image sampling is increased to mitigate phase error, then temporal resolution is improved, but reconstruction time increases and dataset size increases
Solution Approach 1:
The system performs preliminary waveform analysis on the respiratory signal during data acquisition to identify exact timepoints of respiratory phases. This pre-processing step stores the temporal information that will be used later for precise image reconstruction, eliminating the need for post-hoc phase correction and reducing overall reconstruction time while maintaining high temporal resolution
Solution Approach 2:
The patent replaces the traditional mechanical approach of uniformly sampling images at fixed time intervals with a signal-based triggering system. The image reconstruction is synchronized to the actual respiratory waveform, using the extracted respiratory signal to determine when to reconstruct images at specific phases, thereby achieving precise temporal resolution without uniformly increasing sampling frequency
2Measurement precision
If image sampling is increased to mitigate phase error, then temporal resolution is improved, but dataset size increases
Solution Approach 1:
The system pre-identifies and stores the temporal locations of respiratory phases during data acquisition. By having this information ready beforehand, the system can selectively reconstruct images only at the necessary phases without generating excess data, thus achieving high temporal resolution while minimizing dataset size
Solution Approach 2:
The patent changes the sampling strategy from uniform time-based sampling to event-based sampling triggered by respiratory waveform characteristics. This parameter change allows the system to capture images at physiologically relevant moments without uniformly increasing the number of samples, thereby improving temporal resolution without proportionally increasing dataset size
3Measurement precision
If waveform analysis is performed to detect aberrations, then image accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent replaces complex manual phase alignment and post-processing correction methods with an automated waveform analysis system. The computer automatically extracts the respiratory waveform from the acquisition data, identifies phase timepoints, and triggers image reconstruction accordingly, improving image accuracy while keeping processing complexity manageable through automation
Solution Approach 2:
The system performs self-calibration by automatically extracting the respiratory waveform from the acquisition data itself and using this extracted signal to guide the reconstruction process. This self-service approach eliminates the need for separate reference measurements or manual intervention, improving accuracy without requiring additional complex external equipment
Data Source
AI summary
A method includes receiving cine scan data, receiving a plurality of target phases of a periodic waveform, and generating a plurality of images, each image centered at one of the received target phases. A phase shall represent a percentage of a period of a repeating cycle.