Dual Energy CT Contrast Removal Using Segmentation and Extraction
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Solution Overview
Problem
Conventional dual-energy subtraction methods in CT imaging result in poor-quality images with degraded intensity levels and loss of Hounsfield units, making it difficult to effectively remove a selected tissue type or material while maintaining image contrast.
Innovation Solution
The method involves segmenting high and low energy images to isolate contrast agent signals, using a subject mask to identify underlying objects, and performing dual energy subtraction on these segmented images to remove contrast agent signals, while maintaining pixel values in Hounsfield units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If conventional dual energy subtraction is used to remove contrast agent, then the contrast agent signal is removed from the image, but the image quality deteriorates and intensity levels are degraded
Solution Approach 1:
The patent segments the image into contrast agent pixels and non-contrast pixels using a subject mask. This segmentation allows selective processing where only contrast agent pixels are removed while preserving the integrity and quality of non-contrast pixels, thereby maintaining overall image quality while achieving contrast removal.
Solution Approach 2:
The patent extracts and removes only the contrast agent signal from the image by identifying contrast pixels through segmentation and selectively subtracting their contribution. This targeted extraction approach avoids the degradation of overall image quality that occurs with conventional full-image subtraction methods.
2Loss of substance
If conventional dual energy subtraction is used to remove contrast agent, then the contrast agent signal is removed from the image, but Hounsfield units are lost
Solution Approach 1:
By segmenting the image into contrast and non-contrast regions, the patent preserves Hounsfield unit information in the non-contrast regions while only removing contrast agent signals. This segmentation strategy maintains the quantitative integrity of the image data that would otherwise be lost in conventional subtraction methods.
Solution Approach 2:
The patent extracts only the contrast agent component for removal while leaving the non-contrast components intact with their original Hounsfield unit values. This selective extraction preserves the quantitative measurement information (Hounsfield units) for all non-contrast tissues and structures.
3Loss of substance
If conventional dual energy subtraction is used, then contrast agent is removed from the image, but the resulting image has poor quality and degraded intensity levels
Solution Approach 1:
The patent segments the image to identify only contrast agent pixels for removal, preserving the intensity levels of all non-contrast pixels. This selective approach maintains proper brightness and contrast in the final image, avoiding the widespread intensity degradation that occurs with conventional subtraction methods.
Solution Approach 2:
The patent applies different processing treatments to different regions of the image: contrast agent pixels are removed while non-contrast pixels retain their original quality and intensity characteristics. This local quality approach ensures that only the necessary portions are modified while preserving overall image quality.
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 removal of contrast agent signals from CT images, preserving image contrast and intensity levels, enabling clear visualization of underlying objects without the need for separate scans, as demonstrated by improved image quality and accurate representation of pixel values.
Implementation Method 1
The intensity of the transmitted radiation is dependent upon the attenuation of the x-ray beam by the object and each detector produces a separate electrical signal that is a measurement of the beam attenuation
Data Source
AI summary
Contrast from dual energy CT images is removed without affecting other aspects of the image, including objects surrounded by contrast. Dual energy images are acquired during a study of a subject. First, a binary mask image (“Contrast localizer”) is produced to localize the contrast-enhanced areas and build sets of images with contrast-enhanced areas only (“Contrast images”) and complement images with contrast-enhanced areas removed (“Contrast complement images”) for both low and high x-ray beam energy image sets. Only the contrast images are used for dual energy contrast subtraction. Second binary mask image (“Subject localizer”) is produced to localize the objects under study. This mask image is used to reconstruct both low and high energy image sets with contrast selectively removed and subject present.