Medical Image Processing Lesion Extraction via Multi-Stage Evaluation
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Solution Overview
Problem
Conventional methods fail to extract and display lesion candidates of varying sizes with similar forms simultaneously due to differing optimal parameter values for feature amount calculations.
Innovation Solution
A medical image processing device and method that involves a first evaluation for extracting lesion candidate regions, a second evaluation for refining these regions, and a display unit for superimposing the refined regions on a medical image, using a parameter adjustment mechanism to ensure consistent display across different sizes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single parameter value is used for feature amount calculation, then the processing is simple, but lesion candidates of different sizes with similar forms cannot be extracted simultaneously
Solution Approach 1:
The patent divides the lesion candidate extraction process into multiple stages with different parameter settings. A first extracting unit uses initial parameter values to extract candidate regions, while a second extracting unit uses adjusted parameter values to refine the extraction. This segmentation allows the system to handle lesion candidates of various sizes effectively by applying appropriate parameters at each stage.
Solution Approach 2:
The patent implements dynamic parameter adjustment where the parameter values are modified based on the extraction results from the first stage. The second extracting unit adjusts the parameter values (such as form exponent thresholds) according to the characteristics of extracted lesion candidates, enabling the system to adapt to different lesion sizes and forms dynamically during the extraction process.
2Measurement precision
If multiple parameter evaluations are performed, then lesion candidates with similar forms can be extracted, but the processing time increases
Solution Approach 1:
The first extracting unit performs a preliminary extraction using initial parameter values to identify potential lesion candidate regions. This preliminary action filters out obvious non-lesion areas and prepares the data for the second extraction stage, reducing the computational burden and time required for the more precise second evaluation.
Solution Approach 2:
The second extracting unit uses feedback from the first extraction results to adjust parameter values. By analyzing the characteristics of lesion candidates extracted in the first stage, the system dynamically adjusts parameters for the second extraction, improving accuracy while optimizing processing time through intelligent parameter adaptation rather than exhaustive search.
Data Source
AI summary
There is provided a medical image processing device and a medical image processing method that can extract and display lesion candidate regions having different sizes and similarity forms at a time through a series of processing. Therefore, with respect to a first medical image, a first evaluation for the curved surface form of the first medical image is made to extract first lesion candidate regions. With respect to each of the first lesion candidate regions extracted by a first extracting unit, a second evaluation for the curved surface form thereof is made to extract a second lesion candidate region. The second lesion candidate region extracted by a second extracting unit is superimposed and displayed on a second medical image.