Contrast State Determination Using 2D Slice Segmentation
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Solution Overview
Problem
Existing techniques for determining the contrast state in dynamic contrast-enhanced computed tomography images are inefficient, as they require processing three-dimensional images without change and cannot accurately determine the contrast time phase when a specific region is not included in the image.
Innovation Solution
A contrast state determination device and method that acquires and processes multiple two-dimensional images from different positions within a CT image series, estimating index values related to the contrast state and integrating these values to quickly and accurately determine the contrast state, even if an organ is not explicitly included in the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If three-dimensional contrast images are processed without any change, then the contrast state can be determined, but it takes too much time
Solution Approach 1:
The patent segments the three-dimensional contrast image into multiple two-dimensional slice images at different positions. By processing these 2D slices independently and extracting index values from each, the system achieves faster processing while maintaining accurate contrast state determination through integration of multiple slice results.
2Measurement precision
If traditional three-dimensional image processing is used, then the contrast state can be determined, but it cannot accurately determine the contrast time phase when a specific region is not included in the image
Solution Approach 1:
By dividing the 3D image into multiple 2D slices from different positions, the system ensures that even if one slice does not contain a specific organ, other slices may contain it. This segmentation approach improves robustness and accuracy in contrast time phase determination.
Solution Approach 2:
The patent merges the index values extracted from multiple two-dimensional slice images to determine the final contrast state. This combination of results from different slices compensates for missing organs in individual slices and improves overall determination accuracy.
3Productivity
If multiple two-dimensional images are processed from different positions, then the contrast state can be determined quickly and accurately, but the device complexity increases
Solution Approach 1:
The system processes multiple 2D slice images independently, which can be done in parallel, improving processing speed. The segmentation approach allows for efficient computation while maintaining accuracy through integration of results from multiple slices.
Data Source
AI summary
Provided are a contrast state determination device, a contrast state determination method, and a program that quickly, accurately, and robustly determine a contrast state even in a case where there is an organ that is not included in an image. A plurality of two-dimensional images including information of slice images of a subject at different positions are acquired from a first image series captured before or after a contrast agent is injected into the subject, an index value related to a contrast state is estimated from each of the plurality of two-dimensional images, and the contrast state of the first image series is determined on the basis of each of a plurality of the index values.