Image Registration Error Estimation via Excluded Corresponding Points
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Solution Overview
Problem
Current image registration methods in medical imaging struggle to accurately estimate registration errors at arbitrary positions beyond corresponding points, limiting the reliability of lesion identification and comparison across images.
Innovation Solution
An image processing apparatus and method that calculates registration errors by excluding at least one corresponding information item from the plurality of items, allowing for the estimation of registration errors at arbitrary positions based on the calculated errors, using a combination of obtaining, calculating, and estimating units to generate and display error distributions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If registration is performed using all corresponding information items, then registration accuracy is improved, but the ability to estimate error at arbitrary positions deteriorates
Solution Approach 1:
The patent divides the corresponding information items into two groups: a first set used for registration and a second set (excluding at least one item) used for error estimation. This segmentation allows the system to maintain registration accuracy while enabling error estimation at arbitrary positions by using the excluded items as validation data.
Solution Approach 2:
The patent performs preliminary error estimation by calculating registration error at positions of excluded corresponding information items before final registration is completed. This preliminary action allows the system to predict and communicate error characteristics at arbitrary positions, improving reliability while maintaining accuracy.
2Reliability
If corresponding information items are excluded for error calculation, then error estimation at arbitrary positions is improved, but registration accuracy may deteriorate
Solution Approach 1:
The patent segments corresponding information items into a first set for registration and a second set for error estimation. By excluding at least one item from the registration set, the system can calculate registration error at the excluded position and use this to estimate error at arbitrary positions, maintaining both registration accuracy and error estimation capability.
Solution Approach 2:
The patent uses the registration error calculated at excluded corresponding information item positions as an intermediary to estimate error at arbitrary positions. This intermediary error value serves as a bridge between the actual registration error and the estimated error at positions where direct measurement is not possible.
3Adaptability or versatility
If deformation transformation is applied to register images, then lesion identification capability is improved, but registration error increases
Solution Approach 1:
The patent implements feedback by calculating registration error at excluded corresponding information item positions and using this feedback to estimate error at arbitrary positions. This feedback mechanism allows the system to quantify the impact of deformation transformation on registration accuracy, enabling better lesion identification while being aware of potential errors.
Solution Approach 2:
The patent changes the parameter approach by introducing error estimation as a new measurable parameter alongside registration accuracy. By excluding at least one corresponding information item and calculating error at that position, the system can characterize the error introduced by deformation transformation and use this to improve lesion identification reliability.
Data Source
AI summary
An image processing apparatus obtains a plurality of corresponding information items for registration of a first image and a second image of an object, calculates, in a case where the first image and the second image are registered using corresponding information items remaining after excluding at least one corresponding information item from the plurality of corresponding information items, a registration error that occurs at a position of the excluded corresponding information item, and estimates a registration error at an arbitrary position in a case where the first image and the second image are registered using the plurality of corresponding information items based on the calculated registration error.