Contrast Detection in Head CT Scans Using Bright Patches and Sulci
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Solution Overview
Problem
Automated detection of brain bleeds in CT scans is hindered by the uncertainty of whether the scan was taken with or without contrast, as the presence of contrast significantly alters image appearance, leading to incorrect classifications when scans are misinterpreted by AI models trained for non-contrast images.
Innovation Solution
A system that analyzes a head CT scan by selecting a cross-section, determining the presence of contrast based on bright patches and sulci, and assigning priority levels to efficiently determine if the entire scan was taken with or without contrast, allowing for appropriate AI model processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods analyse a large number of cross-sections to determine contrast presence, then detection accuracy is improved, but processing time and computational cost increase significantly
Solution Approach 1:
The patent segments the CT scan into cross-sections and further divides them into groups based on anatomical regions (e.g., brain, neck, chest). Instead of analyzing all cross-sections uniformly, the method selectively samples from specific groups, reducing the total number of cross-sections analyzed while maintaining accurate contrast detection through strategic sampling of representative regions.
Solution Approach 2:
The patent applies different analysis criteria to different anatomical regions. Each region is evaluated based on its specific characteristics (e.g., vascular density in the brain versus soft tissue composition in the chest), allowing optimized detection parameters for each local area rather than using a uniform approach across the entire scan.
2Device complexity
If AI models are trained for non-contrast CT scans only, then model complexity is reduced, but detection reliability decreases when contrast CT scans are misclassified
Solution Approach 1:
The patent performs preliminary analysis of the CT scan to detect the presence of contrast agents before feeding the image to the AI model. This pre-processing step classifies the scan as either contrast-enhanced or non-contrast, allowing the system to route to the appropriate trained model or adjust the analysis parameters accordingly, preventing misclassification of brain bleeds.
Solution Approach 2:
The patent introduces an intermediary contrast detection module that sits between the CT scan acquisition and the AI classification stages. This intermediary component analyzes contrast presence and mediates the workflow by selecting the appropriate AI model or processing parameters, ensuring reliable brain bleed detection regardless of whether contrast was used in the original scan.
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
Enables efficient and accurate determination of whether a CT scan includes contrast, reducing processing time and improving automated image analysis by correctly routing scans to appropriate AI models for classification.
Implementation Method 1
The contrast agent absorbs a high proportion of X-rays. Therefore, when a CT scan takes place, areas with a high concentration of contrast agent (such as blood vessels) absorb more of the X-rays and therefore appear lighter (i.e. have a higher CT number) in the CT scan.
Data Source
AI summary
An apparatus for analysing a head CT scan, where the head CT scan includes a plurality of cross-sections, includes a processor configured to select a first cross-section from among the plurality of cross-sections in the head CT scan; and analyse the first cross-section to determine whether the whole head CT scan was taken with contrast. The analyzing includes determining whether the first cross-section shows contrast, based on a presence of bright patches in the first cross-section, determining whether an amount of sulci in the first cross-section is below a threshold amount. In response to determining that the first cross-section shows contrast, determine that the whole head CT scan was taken with contrast, and in response to the determining that the first cross-section does not show contrast and that the amount of sulci is below the threshold amount determining that the whole head CT scan was taken without contrast.