Spectral CT Data Caching for Faster Multi-Energy Reconstruction
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Solution Overview
Problem
Spectral CT systems face challenges in improving reconstruction efficiency and image quality due to high spatial resolution requirements and large data volumes, particularly in pre-clinical research applications.
Innovation Solution
A method and apparatus for spectral CT imaging that involves caching data frames in memory and storage in an energy-segmented manner, utilizing independent pipeline processes for reconstruction, and employing shared memory and block-wise reading to enhance data access and processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectral CT systems use photon-counting detectors with energy bins for multi-energy imaging, then measurement precision and tissue characterization capability are improved, but data volume and processing complexity increase
Solution Approach 1:
The patent segments the acquired spectral data into multiple energy bins or energy ranges, organizing the large volume of multi-energy data into manageable segments. This segmentation enables independent processing of different energy ranges, reducing the computational complexity while preserving the detailed tissue characterization information obtained from photon-counting detectors
2Manufacturing precision
If spectral micro-CT systems acquire high spatial resolution data for pre-clinical research, then manufacturing precision is improved, but reconstruction time and processing duration increase
Solution Approach 1:
The patent performs preliminary organization and segmentation of the high-resolution spectral data during the acquisition phase, caching data in an energy-segmented manner in memory. This preliminary action prepares the data structure in advance, enabling faster reconstruction processing without compromising the high spatial resolution quality required for pre-clinical research
3Measurement precision
If spectral CT systems store and process large volumes of energy-segmented data frames, then measurement precision is improved, but memory requirements and device complexity increase
Solution Approach 1:
The patent implements segmentation of data frames by energy ranges, storing different energy segments in organized memory structures. This segmentation allows efficient memory management and selective access to specific energy ranges during reconstruction, reducing the overall memory burden while preserving complete spectral information for accurate measurement
Solution Approach 2:
The patent extracts and caches only the necessary data frames in memory in an energy-segmented manner, rather than storing all raw data. This selective extraction reduces memory requirements while ensuring that the essential spectral information needed for precise measurement is readily available for processing
Data Source
AI summary
This disclosure relates to the field of X-ray based medical imaging technology, providing a method, device, and CT scanning imaging system for spectral CT imaging, which may improve the efficiency of reconstructed images. In this disclosure, after obtaining multiple data frames collected by the detector, each data frame is cached in energy segments and stored in memory; Read the data frames required for image reconstruction from memory or disk; Obtain reconstructed images using the read data frames.