Mitral Valve Image Processing for Optimization Speed
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Solution Overview
Problem
Current medical image processing systems for mitral valve simulation face challenges in accurately calculating the valve orifice area, which is crucial for treatment planning in mitral valvuloplasty, due to the complexity of the procedure and the need for precise physical property values, leading to time-consuming optimization calculations.
Innovation Solution
A medical image processing apparatus employing a two-stage algorithm for parameter estimation, which acquires and processes medical images at different time points to estimate simulation parameters efficiently, reducing the time required for optimization calculations by using a loss function that includes the valve orifice area, and correcting shape data to improve parameter estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a two-stage algorithm is used for parameter estimation, then the time required for optimization calculations is reduced, but the complexity of the processing procedure increases
Solution Approach 1:
The parameter estimation process is divided into two distinct stages: a first stage that estimates initial parameter values using simplified methods, and a second stage that refines these values using optimization calculations. This segmentation allows the system to reduce computational time by avoiding unnecessary complex calculations while maintaining accuracy through the refined second stage.
2Measurement precision
If the loss function includes the valve orifice area, then the prediction accuracy is improved, but the calculation time increases
Solution Approach 1:
The system performs preliminary actions by estimating initial parameter values in the first stage before performing the time-consuming optimization calculations in the second stage. This preliminary estimation using the loss function that includes valve orifice area allows the system to guide the optimization process more efficiently, reducing overall calculation time while maintaining high prediction accuracy.
3Measurement precision
If shape data is corrected to improve parameter estimation accuracy, then the prediction accuracy is improved, but the processing time increases
Solution Approach 1:
Shape data correction is performed as a preliminary action in the first stage of parameter estimation. By correcting the shape data before the optimization calculations, the system ensures that accurate parameter values are obtained from the beginning, reducing the need for iterative corrections and thereby minimizing the overall processing time while maintaining high accuracy.
Data Source
AI summary
A medical image processing apparatus includes processing circuitry. The processing circuitry acquires first feature data related to the structure of interest from first medical image data scanned at a first timing and second feature data related to the structure of interest from second medical image data scanned at a second timing, estimates the third feature data by estimating the structure of interest at the second timing by simulation based on the first feature data, and calculates a first feature value and a second feature value that is a local feature value more than the first feature value from the second feature data and the third feature data. The processing circuitry specifies a plurality of parameter sets based on optimization calculation having a loss function including the first feature value, and determines a parameter set of interest from the plurality of parameter sets based on the second feature value.