CT Image Processing for Accurate Target Region Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current CT image processing techniques fail to accurately highlight and display target regions in CT images, leading to incomplete information and misjudgments, especially in complex images like those from abdominal scans, due to blurring tissue boundaries and overlapping tissue densities.
Innovation Solution
A CT image processing method and apparatus that separates target regions by judging CT values of voxel points, removes false positives, and performs volume rendering to enhance border points, allowing for accurate three-dimensional display and measurement of characteristic data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CT images are processed using traditional image processing techniques, then the processing speed is maintained, but the target regions cannot be highlighted accurately and the detection precision deteriorates
Solution Approach 1:
The patent changes the parameter of region separation from traditional intensity-based segmentation to CT value-based segmentation. By using the specific parameter of CT values (Hounsfield units) to identify target regions, the system achieves accurate detection of pathological areas while maintaining processing efficiency through automated threshold-based classification.
Solution Approach 2:
The patent introduces an intermediary computational layer that automatically identifies and separates target regions based on CT value analysis. This intermediary processing step acts as a mediator between raw CT images and final diagnostic display, accurately highlighting target regions without requiring manual intervention or sacrificing processing speed.
2Loss of information
If CT images display all tissue regions, then comprehensive information is provided, but the target regions are not highlighted and information completeness deteriorates
Solution Approach 1:
The patent extracts target regions from the complex CT images by automatically identifying and separating areas with abnormal CT values. This extraction process isolates pathological information from the background tissue, ensuring complete pathological information is captured and highlighted without requiring complex manual processing.
Solution Approach 2:
The patent segments the CT image into different regions based on CT value thresholds, separating target regions (pathological areas) from normal tissue. This segmentation approach ensures that all relevant pathological information is captured and displayed prominently, reducing information loss while maintaining manageable processing complexity through automated methods.
3Measurement precision
If doctors manually analyze CT images, then detailed observation is possible, but the detection time increases and accuracy deteriorates due to human error
Solution Approach 1:
The patent implements a self-service automated system that performs target region identification and separation without requiring manual doctor intervention. The system automatically analyzes CT values, identifies pathological regions, and highlights target areas, eliminating human error while maintaining rapid detection speeds and improving overall diagnostic accuracy.
Solution Approach 2:
The patent replaces the mechanical process of manual image analysis with an automated computational system. By substituting human visual inspection with algorithm-based CT value analysis, the system achieves consistent high accuracy without detection time delays or human error, while preserving all necessary pathological information.
Data Source
AI summary
The present invention discloses apparatus, method, and system for CT image processing; said apparatus comprises: an interface unit for obtaining CT images; a target region separation unit for separating said target region from the CT images by means of judging the CT values of voxel points in said CT images, wherein points with CT values greater than or equal to the threshold for target region separation constitute the target region, and said target region comprises at least one separate region; a false positive region removing unit for removing false positive regions from said target region and obtaining the accurate target region. The present invention can be used to quickly and conveniently determine the target region to be detected, measure the characteristic data of the target region, and display the physical and relative positions of the target region in a three-dimensional manner; with a lower threshold for target region separation, the present invention can reduce the omission rate of detection; in addition, on that base, the present invention can remove possible false positive regions, thereby describing the target region accurately and improve accuracy of target information.