Fibonacci-Based Projection Data Acquisition for CT Image Homogeneity
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Solution Overview
Problem
Existing computed tomography systems face challenges in achieving high image quality due to inhomogeneous distribution of projection data, particularly when acquiring data over few rotations, leading to low image quality in reconstructed CT images.
Innovation Solution
A projection data acquisition apparatus that uses a radiation source and detector to acquire data at specific rotational positions, where the angular distances between acquisition positions follow Fibonacci numbers, dividing the largest non-acquisition angular regions into two smaller regions, ensuring homogeneous distribution across acquisition intervals and improving image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If projection data are acquired only at certain rotational positions during few rotations, then the acquisition time is reduced, but the projection data become inhomogeneously distributed leading to low image quality
Solution Approach 1:
The acquisition process is segmented into multiple acquisition intervals, with each interval acquiring data at specific rotational positions determined by Fibonacci numbers. This segmentation allows efficient sampling across few rotations while maintaining homogeneous distribution of projection data through the mathematical properties of Fibonacci sequences.
Solution Approach 2:
The rotational positions for data acquisition are dynamically determined using Fibonacci number sequences. The first acquisition rotational position of each interval is calculated as (n times the (k-1)-th Fibonacci number) modulo the k-th Fibonacci number, where n is the interval number. This parameter change strategy ensures homogeneous angular distribution of projection data while completing acquisition in few rotations.
2Stability of the object's composition
If projection data are acquired at evenly spaced rotational positions, then the data distribution is uniform, but the angular coverage is insufficient when acquiring over few rotations
Solution Approach 1:
The patent introduces a temporal dimension to the angular sampling by using Fibonacci sequences that evolve across multiple acquisition intervals. Instead of simple even spacing in one dimension, the Fibonacci-based positioning creates a two-dimensional sampling pattern (angular position × interval number) that achieves both uniform distribution and comprehensive angular coverage.
Solution Approach 2:
The acquisition rotational positions are determined by changing parameters based on the interval number n. The formula (n × F(k-1)) mod F(k) dynamically adjusts the starting position of each acquisition interval, ensuring that over few rotations, the cumulative angular coverage is maximized while maintaining uniform data distribution across all intervals.
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 the reconstruction of computed tomography images with improved quality by ensuring that acquisition rotational positions are uniformly distributed, enabling high-quality image reconstruction from any angular range.
Implementation Method 1
a radiation source for generating radiation for traversing the object, a detector for detecting the radiation after having traversed the object and for generating the projection data based on the detected radiation
Data Source
AI summary
The invention relates to a projection data acquisition apparatus (14) for acquiring projection data for being used for reconstructing a computed tomography image. In acquisition intervals projection data are acquired only at certain acquisition rotational positions of a radiation source (2) relative to an object, wherein an acquisition rotational position of a current acquisition interval divides a largest non-acquisition angular region covering rotational positions, at which projection data have not already been acquired, into two smaller non-acquisition angular regions. Because of this acquisition of the projection data, after each acquisition interval the acquisition rotational positions, at which projection data have been acquired already, are relatively homogeneously distributed. This allows for an improved image quality of a computed tomography image which is reconstructed based on the acquired projection data.