Lesion Diagnosis via 4D Data Representation
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Solution Overview
Problem
In medical imaging, particularly MRI, it is challenging to accurately distinguish between benign and malignant lesions due to transformations from source signal to image intensity, which can vary and obscure the original signal strength, making comparative analysis difficult and prone to errors.
Innovation Solution
The method involves generating display data by using thresholding and clustering algorithms to create regions of interest (ROIs) around lesions, analyzing the number of steps in ROI area vs. intensity plots, which is highly predictive of lesion type, and is relatively insensitive to intensity transformations like windowing and leveling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If linear transformations (windowing and leveling) are applied to transform source signal to image intensity signal, then medical diagnosis optimization is improved, but the ability to evaluate original signal strength and perform comparative analysis deteriorates
Solution Approach 1:
The patent extends the data representation from 3 dimensions (x, y, w) to 4 dimensions (x, y, z, w), where the fourth dimension preserves the original source data values. This additional dimension allows simultaneous display of both transformed image intensity data and original source signal strength without interference, enabling radiologists to perform comparative analysis while maintaining diagnostic optimization.
2Measurement precision
If case-specific transformations are applied to optimize image intensity for each case, then diagnostic accuracy for individual cases is improved, but consistency across cases and ability to compare lesions deteriorates
Solution Approach 1:
The patent introduces an intermediary representation in the fourth dimension that preserves the original source data values unchanged. This intermediary layer acts as a stable reference that maintains consistency across different cases, allowing radiologists to compare lesions from different patients using the same original signal strength scale while still benefiting from case-specific optimizations in the primary image display.
3Ease of operation
If windowing and leveling operations are applied to adjust intensity values, then display system limitations are addressed, but the original signal strength information becomes obscured
Solution Approach 1:
The patent segments the data representation into two distinct components: the primary 3D volume data (x, y, z) that undergoes windowing and leveling transformations for display compatibility, and a separate 4th dimension (w) that preserves the original source data values unchanged. This segmentation allows each component to serve its specific purpose without compromising the other.
Data Source
AI summary
A method of aiding in the evaluation of lesions in a body using a plurality of sets of image data of sections of the body region in mutually parallel planes. Processing of the data requires several steps, including pixel intensity pattern recognition, ˜ contouring of the regions of probable pathology, thresholding and 3-dimensional clustering, providing each pixel with a color representative of a selected opacity level and displaying an image of the region of interest where areas of probable pathological conditions are highlighted.