3D CT Tumor Progression Tracking With Computational Phantom Matching
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Solution Overview
Problem
Existing systems struggle to accurately track the progression of tumors over time, necessitating improved methods for tracking tumor size, number, and new lesion occurrence, while reducing reading errors in medical imaging.
Innovation Solution
A method and system for generating 3D modeling images from CT scans, tracking changes over time, and schematizing time series data to confirm tumor progression, utilizing computational phantom images for tissue matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking of tumor size and number is performed on CT images, then reading accuracy may be compromised by human error, but automated systems lack the ability to accurately track tumor progression over time
Solution Approach 1:
The patent introduces a computational phantom as an intermediary reference model that mediates between automated image processing and accurate tumor tracking. The phantom provides a standardized anatomical framework that enables consistent identification and measurement of tumors across multiple time points, eliminating both manual reading errors and automated tracking inaccuracies
Solution Approach 2:
The patent creates a digital copy of the patient's anatomy through a computational phantom that can be repeatedly measured and compared. This virtual model serves as a permanent reference that can be overlaid with new imaging data to accurately track tumor progression without the variability of manual measurement
2Loss of information
If 3D modeling images are generated from CT scans to track tumor changes, then tumor progression can be visualized, but the complexity of processing and analyzing the data increases
Solution Approach 1:
The patent segments the complex 3D modeling process into distinct functional modules: CT image acquisition, computational phantom generation, image registration, tumor detection, and progression analysis. This segmentation allows each module to be optimized independently and simplifies the overall processing pipeline while preserving all tumor progression information
3Measurement precision
If computational phantom images are used to match subject images for tissue comparison, then tissue changes can be detected, but the time required for image matching and analysis increases
Solution Approach 1:
The patent performs preliminary actions by pre-generating computational phantom images and establishing reference anatomical models before actual tumor tracking begins. The phantom is created once and can be reused for multiple comparisons, significantly reducing the time required for subsequent image matching while maintaining high precision in tissue change detection
Data Source
AI summary
The present disclosure relates to a method for tracking a tumor in a CT image and a system for diagnosing using the same. The method for tracking tumor includes the operations of: generating a 3D modeling image including at least one characteristic area in a subject's body based on the CT image of the subject; tracking a change according to a flow of time in the 3D modeling image with respect to the subject's characteristic area to generate time series data; and schematizing the time series data.