CT Image Analysis for Brain Infarction Volume Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current MRI technologies are time-consuming and costly, and CT imaging struggles to accurately identify infarction volumes, while posing risks for patients with pacemakers or ferromagnetic implants, and failing to provide timely aid for acute infarct strokes.
Innovation Solution
A system and method for analyzing brain tissue using computerized tomographic imaging, involving a processor and memory circuit that aligns, enhances, and smooths CT images, and utilizes a trained neural network to generate a t-score map for infarction volume identification, improving image resolution and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If MRI technology is used to scan the patient's brain, then the image quality and diagnostic accuracy are improved, but the scanning time is extended (more than 10 minutes) and the cost increases
Solution Approach 1:
The patent uses CT imaging instead of MRI, accepting lower inherent image quality but compensating through rapid acquisition (seconds vs. 10+ minutes) and post-processing enhancement. The 'disposable' nature refers to using a faster, less expensive modality (CT) that can be discarded in favor of more advanced imaging only when absolutely necessary, rather than always using the superior but slower MRI.
Solution Approach 2:
The system performs preliminary image preprocessing operations (normalization, skull stripping, tissue segmentation) on the CT images before final analysis. This preliminary enhancement of the CT images allows the system to achieve diagnostic accuracy comparable to MRI while maintaining the speed advantage of CT scanning.
2Productivity
If CT imaging is used to scan the patient's brain, then the scanning time is reduced (several seconds), but the ability to accurately identify infarction volume is insufficient
Solution Approach 1:
The patent introduces multiple intermediary processing steps between the raw CT image and the final infarction volume identification: normalization to standard brain space, skull stripping to remove bone interference, tissue segmentation to separate different brain tissues, and comparison with control group data. These intermediaries transform the limited CT data into diagnostically useful information.
Solution Approach 2:
The patent replaces manual radiological assessment with an automated computerized analysis system that uses algorithms for image normalization, segmentation, and statistical comparison. This mechanical/automated substitution enables accurate infarction volume measurement from CT images that would be difficult to assess reliably by human visual inspection alone.
3Measurement precision
If MRI is used for patients with pacemakers or ferromagnetic implants, then diagnostic accuracy is maintained, but safety risks arise due to contraindications
Solution Approach 1:
The patent uses CT imaging as a safe alternative for patients with pacemakers or ferromagnetic implants. While CT has lower soft-tissue contrast than MRI, the system compensates through post-processing enhancement techniques, making it suitable for this vulnerable patient population without exposing them to the safety risks of MRI.
4Productivity
If direct identification of infarction volume from original CT images is attempted, then the process is simple and fast, but the identification accuracy is insufficient
Solution Approach 1:
The system performs preliminary processing steps (normalization, skull stripping, segmentation) automatically and efficiently before final infarction volume identification. These preprocessing operations are computationally optimized to maintain fast processing while significantly improving the accuracy of infarction detection compared to direct visual assessment of raw images.
Data Source
AI summary
The present disclosure provides an operating method of a system for analyzing brain tissue based on computerized tomographic imaging, and the operation method includes steps as follows. A computed tomography image of a subject is aligned to a predetermined standard brain space image, to obtain a first normalized test computed tomography image. A voxel contrast of the first normalized test computed tomography image is enhanced to obtain an enhanced first normalized test computed tomography image. The enhanced first normalized test computed tomography image is aligned to an average computed tomographic image of a control group to obtain a second normalized test computed tomography image. An analysis based on the second normalized test computed tomography image and a plurality of computerized tomographic images of the control group is performed to obtain a t-score map.


