Medical Image Volume Calculation Using Connected Point Labeling
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Solution Overview
Problem
Current methods for calculating volumes in medical images, such as MRI, are inaccurate due to reliance on 2D tools and manual extrapolation, leading to significant measurement uncertainties and errors in 3D volume calculations.
Innovation Solution
A method is introduced that involves labeling connected points in images, superimposing and correlating common and non-common parts between images, and assigning labels to determine volumes accurately, using segmentation, variance filtering, and region filling techniques to improve precision and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 2D measurement tools and manual extrapolation are used to calculate volumes in medical images, then the measurement process is simple to operate, but the measurement precision and reliability are poor due to significant delta errors in 3D volume calculations
Solution Approach 1:
The patent transitions from 2D manual measurements to 3D automated volume calculations by processing sequences of 2D medical images through digital reconstruction. The system stacks and processes multiple 2D slices to create 3D volumetric representations, enabling precise volume measurements that overcome the limitations of 2D extrapolation methods.
Solution Approach 2:
The patent replaces manual mechanical measurement tools (rulers, calipers) with automated digital image processing algorithms. The system uses computer-based segmentation, registration, and volume calculation algorithms to automatically determine anatomical volumes from medical images, eliminating manual measurement errors and improving precision.
2Productivity
If manual volume calculation methods are used, then the device complexity is low, but the time required for analysis is excessive and productivity is reduced
Solution Approach 1:
The patent implements automated self-service processing where the system automatically performs image segmentation, registration, and volume calculation without requiring manual intervention at each step. The algorithms autonomously process the medical images and generate volumetric measurements, significantly improving analysis speed and productivity.
Solution Approach 2:
The patent performs preliminary processing steps such as image preprocessing, noise reduction, and initial segmentation before the main volume calculation. This preliminary action prepares the data in advance, enabling faster and more accurate final measurements while reducing the complexity of the main processing step.
3Reliability
If 2D measurement tools are used for volume calculation, then the ease of operation is high, but the reliability of medical decision-making is compromised due to amplified delta errors
Solution Approach 1:
The patent introduces digital image processing algorithms as an intermediary between the raw medical images and the final volume measurements. This intermediary layer performs automated segmentation and registration, providing reliable and reproducible measurements that enhance diagnostic reliability while maintaining operational simplicity through automated workflows.
Data Source
AI summary
A method to transmit a label between two images, characterized in that the method includes the following steps:providing a first image, the first image comprising several sets of connected points, each set being characterized by a label,providing a second image,from the second image, determining several sets of connected points,superimposing the two images to determine the common parts and non-common parts of the sets in the first and second image,giving each common part of the second image, the label of the set in the first image with which said part is common,giving each non-common part of the second image in contact with a single set of connected points in the first image, the label of said set,giving a new label to each non-common part of the second image not in contact with any set in the first image.