CT Tube Current Modulation by Patient Size
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Solution Overview
Problem
Computed tomography (CT) imaging systems face challenges in maintaining consistent image quality across varying patient sizes, leading to image degradation or excessive x-ray exposure, as existing systems fail to adjust noise levels effectively based on patient size.
Innovation Solution
A method and system that utilize a processor to adjust noise in medical imaging systems by calculating a noise index based on patient size, adjusting tube current, and selecting appropriate filter parameters and kilovolt peak potentials to optimize image quality and reduce x-ray dose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the same tube current is applied to all patients regardless of size, then the imaging system operation is simple, but image quality degrades for larger patients and x-ray dose increases for smaller patients
Solution Approach 1:
The patent implements dynamic tube current modulation based on patient size classification. The system automatically adjusts tube current parameters according to detected patient characteristics (small, medium, large categories), transforming the static fixed tube current into a dynamic adaptive parameter that optimizes image quality for different patient sizes while maintaining automated operation.
Solution Approach 2:
The patent changes the tube current parameter based on patient size. By classifying patients into size categories and applying different tube current levels to each category, the system optimizes the balance between image quality and radiation dose. This parameter adjustment resolves the contradiction by maintaining simple automated operation while improving image quality consistency across different patient sizes.
2Reliability
If tube current is increased to scan larger patients, then image quality improves for larger patients, but smaller patients are exposed to excessive x-ray dose
Solution Approach 1:
The patent applies local quality by tailoring tube current parameters to specific patient size categories. Instead of using a uniform high tube current for all patients, the system applies appropriate tube current levels customized to each patient's size category (small, medium, large), thereby optimizing image quality for each group while minimizing unnecessary radiation dose exposure, particularly for smaller patients.
Solution Approach 2:
The patent implements parameter changes by adjusting tube current based on patient size classification. The system modifies the tube current parameter dynamically according to the detected patient characteristics, applying higher currents only when necessary for larger patients while using lower currents for smaller patients, thus balancing image quality requirements with radiation dose minimization.
3Object-affected harmful factors
If tube current is decreased to scan smaller patients, then x-ray dose is reduced, but image quality becomes insufficient for larger patients
Solution Approach 1:
The patent applies local quality by providing differentiated tube current settings for different patient size categories. The system recognizes that smaller patients require lower tube currents to minimize dose, while larger patients require higher tube currents to maintain adequate image quality. This localized parameter adjustment ensures that each patient group receives appropriate imaging parameters tailored to their specific needs.
Solution Approach 2:
The patent implements dynamics by making the tube current parameter adaptive rather than fixed. The system dynamically adjusts the tube current based on real-time patient size detection, allowing the imaging parameters to change according to the specific patient being scanned. This dynamic adjustment resolves the contradiction by ensuring sufficient image quality for larger patients while minimizing dose for smaller patients through automated parameter modification.
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
The system effectively adjusts noise levels and optimizes image quality by calculating adjustments based on patient size, ensuring consistent image quality across different patient sizes while minimizing x-ray exposure.
Implementation Method 1
a scintillator for converting X-rays to light energy adjacent the collimator
Implementation Method 2
and photodiodes for receiving the light energy from the adjacent scintillator
Implementation Method 3
X-ray sources typically include X-ray tubes, which conduct a tube current and emit the X-ray beam at a focal point
Data Source
AI summary
A method for adjusting noise in an imaging system is described. The method includes adjusting, by a processor, a noise within an image based on a patient size.