Histogram Calculation for Auto-Windowing Collimated X-ray Image
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Solution Overview
Problem
Conventional X-ray imaging systems face challenges in accurately calculating histograms for automatic window level adjustments due to inclusion of pixels from collimated areas, leading to skewed images and decreased contrast, especially in angiographic imaging.
Innovation Solution
An X-ray diagnostic imaging system that excludes pixels from the collimated area from histogram calculations, using a system controller and image processing chain to generate a novel histogram that improves image processing and contrast by distinguishing between region of interest and collimated area pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixels from collimated areas are included in histogram calculations, then the histogram represents the entire image area, but the histogram becomes skewed and image contrast decreases
Solution Approach 1:
The patent extracts and excludes pixels from collimated areas from the histogram calculation process. The system identifies collimated area pixels through collimator position information and electronic shutter data, then removes these pixels from the dataset used for histogram generation. This extraction principle directly resolves the contradiction by eliminating the harmful influence of collimated pixels on histogram accuracy while preserving the beneficial representation of the region of interest.
Solution Approach 2:
The patent segments the image into distinct regions: collimated area pixels and non-collimated area pixels. By using collimator position information and electronic shutter blanking data, the system divides the pixel population into separate groups, allowing independent processing. The histogram is calculated only from the non-collimated segment, ensuring accuracy while maintaining image contrast in the displayed region of interest.
2Manufacturing precision
If manual collimator adjustment is performed at each station, then collimator settings can be optimized for each image, but the process becomes cumbersome and time consuming
Solution Approach 1:
The system implements automatic collimator adjustment that performs self-service functionality. The collimator position is automatically set based on pre-stored position information corresponding to different imaging stations and procedures. This eliminates the need for manual adjustment at each station while maintaining optimized collimator positioning for each specific imaging task, thereby reducing setup time without sacrificing positioning accuracy.
Solution Approach 2:
The patent employs preliminary action by pre-storing collimator position information for various imaging stations and procedures before actual image acquisition. The system prepares collimator settings in advance according to the specific angiographic procedure to be performed, so that when imaging begins, the collimator is already positioned optimally without requiring manual adjustment during the procedure.
3Area of stationary object
If black borders from collimated pixels are included in the displayed image, then the complete detector area is visualized, but post-acquisition processing is affected and image quality decreases
Solution Approach 1:
The patent extracts and removes black border pixels from the displayed image output. Using electronic shutter blanking information, the system identifies pixels corresponding to collimated areas and excludes them from the final image display. This extraction principle eliminates the harmful black borders that would otherwise degrade image quality and interfere with post-acquisition processing, while maintaining accurate representation of the region of interest.
Solution Approach 2:
The patent applies local quality by differentiating between regions that should be displayed and those that should be excluded. The electronic shutter defines specific regions (collimated areas) with different quality requirements. By applying different processing rules to different regions - displaying non-collimated pixels with full quality while excluding collimated pixels - the system optimizes overall image quality without unnecessarily reducing the displayed area.
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 enhances image quality by providing improved statistical-based processing and contrast adjustment, ensuring accurate window level settings and compliance with regulatory requirements by clearly identifying collimated area pixels in the displayed image.
Implementation Method 1
an X-ray source for controlling an X-ray beam radiated towards a patient under examination
Implementation Method 2
the X-ray source comprises an X-ray tube and X-ray collimator assembly
Implementation Method 3
An X-ray imaging device or detector is arranged for receiving the X-ray beam after it has passed through the patient to acquire latent image frames
Data Source
AI summary
An X-ray diagnostic imaging system is disclosed that includes an X-ray source for controlling an X-ray beam radiated towards a patient under examination. The X-ray source includes an X-ray tube and X-ray collimator assembly. The system includes an-ray imaging device arranged for receiving the X-ray beam after is has passed through the patient to acquire latent image frames of a region of interest (ROI) of the patient's anatomy, and a system controller coupled to X-ray source and X-ray imaging device for controlling latent image frame acquisition and post-acquisition processing. The controlling includes controlling the X-ray imaging device and X-ray positioning, and collimator assembly operation. An image processing chain including an image processor coupled to the system controller, receives latent image frames from the X-ray imaging device for processing, including calculating a histogram from which pixels within a collimated area are removed. The improved histogram is used in post-acquisition processing such as a window level setting. An X-ray image processed by functions using the improved histogram is displayed by a display device coupled to the image processing chain.