CT Image Temporal Resolution via Motion Region Segmentation
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Solution Overview
Problem
Current CT imaging systems face challenges in minimizing motion blurring, particularly in cardiac imaging, due to the limitations of gantry speed and the high cost of two-tube-two-detector systems, which affect the temporal resolution of x-ray images.
Innovation Solution
A method and apparatus that acquire and process CT data by identifying subsets of data representing static and moving regions within an object, iteratively updating image data corresponding to motion regions, and reconstructing images using both updated and non-updated data to enhance temporal resolution without requiring significant increases in gantry speed or x-ray tube power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If gantry speed is increased to decrease acquisition time, then temporal resolution is improved, but device complexity and cost increase due to mechanical limitations
Solution Approach 1:
The patent segments the CT data into multiple subsets (first subset, second subset, third subset) corresponding to different time periods within the acquisition window. By processing these subsets separately and combining them, the system achieves improved temporal resolution without requiring faster gantry rotation, thus avoiding mechanical complexity limitations.
Solution Approach 2:
The patent dynamically adjusts the acquisition window and selectively updates image data based on motion detection in different temporal subsets. This dynamic approach allows the system to adapt to varying motion conditions without changing the physical gantry speed, resolving the contradiction between time resolution and mechanical constraints.
2Loss of time
If two-tube-two-detector approach is used to minimize blurring, then temporal resolution is improved, but device complexity and cost increase significantly
Solution Approach 1:
Instead of using two physical tube-detector systems, the patent segments a single CT dataset into multiple temporal subsets and processes them independently. This software-based segmentation achieves the temporal resolution benefits of multiple systems without the corresponding hardware complexity and cost.
Solution Approach 2:
The patent creates multiple virtual copies of the imaging system through computational processing of different data subsets. By reconstructing images from temporally separated subsets and combining them, it simulates the effect of multiple simultaneous imaging systems without duplicating the physical hardware.
3Loss of time
If more powerful x-ray tubes are used to maintain image quality during reduced acquisition time, then temporal resolution is improved, but device complexity and cost increase
Solution Approach 1:
The patent dynamically selects and updates image data from different temporal subsets based on detected motion, rather than requiring uniformly high power throughout the acquisition. This allows standard x-ray tubes to maintain image quality by processing data intelligently across multiple time periods rather than demanding higher instantaneous power.
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 effectively reduces motion artifacts, improving the temporal resolution of CT images by isolating and updating only the image data affected by motion, thereby reducing processing time and maintaining image quality with fewer projection views.
Implementation Method 1
an x-ray source emits a fan-shaped or cone-shaped beam toward a subject or object... The beam, after being attenuated by the subject, impinges upon an array of radiation detectors
Implementation Method 2
a scintillator for converting x-rays to light energy adjacent the collimator
Implementation Method 3
photodiodes for receiving the light energy from the adjacent scintillator and producing electrical signals therefrom
Data Source
Figure 1~2
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Figure 5~6
AI summary
A system, method, and apparatus includes a computed tomography (CT) system having a rotatable gantry, an x-ray source, a generator, a detector having pixels and positioned to receive x-rays, and a computer. The computer is programmed to acquire (102) CT data representative of an object, determine (112) a first subset of the CT data, determine (114) a second subset of the CT data, and determine (124) a difference between the first and second subsets of the CT data to identify a motion region in the object. The computer is also programmed to update (126) image data reconstructed from a first portion of the first subset of the CT data and corresponding to the region and reconstruct (128) an image based on the updated image data and non-updated image data. The non-updated image data is reconstructed from a second portion the first subset of the CT data.