Shadow Region Detection in Contrast Enhanced Liver CT Scans
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Solution Overview
Problem
Current methods for extracting shadow regions from contrast enhanced three-dimensional images obtained at different time points are inefficient, leading to increased radiological reading burden and inaccurate tumor detection in medical imaging, particularly in liver CT scans.
Innovation Solution
An image processing apparatus and method that includes a first shadow region detection unit for identifying shadow regions in two-dimensional images at one time point and a second shadow region detection unit using position information to detect corresponding shadow regions in images from different time points, employing graph cut region segmentation and alignment techniques to enhance accuracy and reduce manual input operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If shadow region detection is performed on each contrast enhanced three-dimensional image obtained at different time points, then tumor detection accuracy is improved, but the amount of data processing and reading time increases dramatically
Solution Approach 1:
The patent segments the detection process into two stages: first detecting shadow regions in 2D images at specific time points, then using those results to guide detection in 3D images. This segmentation reduces the computational burden while maintaining detection accuracy across multiple time points.
Solution Approach 2:
The patent performs preliminary detection of shadow regions in 2D images before processing 3D images. By pre-identifying potential tumor regions in 2D images, the system can focus subsequent 3D analysis on relevant areas, reducing overall processing time while maintaining accuracy.
2Reliability
If contrast enhanced three-dimensional images are obtained at multiple time points to observe temporal changes, then tumor detection capability is improved, but the radiological reading burden increases to several times
Solution Approach 1:
The patent uses 2D images as an intermediary between the raw 3D contrast enhanced images and the final tumor detection. The 2D images serve as a mediator that simplifies the detection process by providing a more manageable format for initial shadow region identification, reducing the reading burden while maintaining detection capability.
Solution Approach 2:
The patent extracts shadow region information from the complex 3D contrast enhanced images by projecting or selecting specific 2D slices. This extraction isolates the critical tumor detection information from the overwhelming 3D data, reducing the reading burden to a manageable level while preserving detection capability.
3Ease of operation
If manual detection methods are used for shadow regions, then operational flexibility is maintained, but processing efficiency and accuracy are reduced
Solution Approach 1:
The patent implements an automated detection system that performs shadow region identification without requiring manual intervention. The system self-processes the contrast enhanced images by automatically detecting shadow regions in 2D images and extending this detection to 3D images, significantly improving processing efficiency while maintaining operational flexibility through automated algorithms.
Data Source
AI summary
A shadow region extraction method capable of extracting a shadow region from contrast enhanced three-dimensional images obtained at different time points in an improved manner. The method includes the steps of detecting a first shadow region from a contrast enhanced two-dimensional image constituting a contrast enhanced three-dimensional image obtained at a first time point among a plurality of contrast enhanced three-dimensional images of a subject obtained at different time points, detecting, by the use of position information of a point in the first shadow region, a second shadow region corresponding to the first shadow region from a contrast enhanced two-dimensional image constituting a contrast enhanced three-dimensional image obtained at a second time point different from the first time point, and displaying the first shadow region and the second shadow region.