Spectral CT Motion Correction via Energy-Level Contrast
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Solution Overview
Problem
Current motion correction methods for computed tomography (CT) images, particularly in cardiac imaging, face challenges due to the rapid movement of the heart, requiring complex and error-prone segmentation to isolate moving structures, which can lead to motion artifacts and inefficient scan processes.
Innovation Solution
The method employs spectral CT data to identify moving structures by selecting energy levels that provide high contrast, allowing for material decomposition and the calculation of a motion vector field, thereby simplifying motion correction and reducing calculation effort and error risk, enabling motion-corrected CT images with reduced scan time and improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex segmentation methods are used to isolate moving structures for motion correction, then motion correction accuracy is improved, but device complexity and error risk increase
Solution Approach 1:
The patent extracts only the necessary information (motion vectors) directly from the raw spectral CT data without performing complex segmentation. By using material decomposition to isolate specific materials (e.g., iodine contrast) and directly computing motion vectors from their attenuation patterns, the method obtains motion correction data while avoiding the complex and error-prone segmentation process entirely.
2Area of stationary object
If multiple stacks of axial images are acquired to cover large examination areas, then measurement coverage is improved, but motion artifacts increase due to patient movement between acquisitions
Solution Approach 1:
The patent combines motion correction information across multiple stacks of axial images by computing motion vectors for each stack and then integrating them through rigid or non-rigid registration. This allows large examination areas to be covered while correcting for patient movement between acquisitions, thereby reducing motion artifacts that would otherwise occur with multiple separate scans.
3Loss of time
If scan time is reduced to minimize heart movement during cardiac CT, then motion artifacts are reduced, but image quality and contrast resolution deteriorate
Solution Approach 1:
The patent performs material decomposition and motion vector calculation during the scan acquisition process itself, rather than as separate post-processing steps. By preparing the data structures and computing preliminary motion parameters in real-time or near-real-time during the scan, the method enables longer scan durations without compromising image quality, as the motion correction is already integrated into the acquisition workflow.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for robust motion correction, enabling longer scan times, potentially eliminating the need for sedation, reducing X-ray dose, and avoiding repeat scans, while improving image quality and reducing the risk of motion artifacts.
Implementation Method 1
the CT image only shows the adsorption or Attenuation of photons in a specific energy range
Implementation Method 2
Some CT scanners allow the acquisition of energy-sensitive computed tomography (CT) data
Data Source
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AI summary
The invention relates to a method for motion correction of computed tomography images, comprising the following steps: a) providing spectral CT data (20) of an examination area (10) with a moving object (12), wherein the spectral CT data were acquired with an energy-sensitive CT device (1) and contain CT data of at least one energy level, and wherein at least one energy level of the CT data is adapted to a structure (14) in the moving object; b) identifying the structure (14) in the CT data from the energy level(s) adapted to the structure; c) calculating a motion vector field (24) of the identified structure (14); d) motion correction of the spectral CT data by the motion vector field and calculation of a motion-corrected CT image.