Tomosynthesis Imaging Support Apparatus Body Movement Correction
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Solution Overview
Problem
Tomosynthesis imaging faces challenges in accurately estimating and preventing body movement during imaging, leading to blurred images, particularly in breast cancer detection, due to mechanical errors and subject movement.
Innovation Solution
A tomosynthesis imaging support apparatus that acquires subject and imaging condition information, derives body movement feature information, and stores correspondence data to provide imaging advice, utilizing a database or learned models to estimate and correct for body movement, thereby improving image clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If tomosynthesis imaging is performed by moving the radiation source to multiple positions, then tomographic images can be generated to separate overlapping structures, but body movement occurs during the imaging process causing image blur
Solution Approach 1:
The system performs preliminary actions by acquiring subject information, imaging condition information, and positioning information before tomosynthesis imaging to predict and estimate body movement. This allows the system to prepare correction strategies in advance, addressing the contradiction between achieving clear tomographic images and preventing motion blur during the imaging process.
Solution Approach 2:
The system implements feedback by acquiring actual body movement information during imaging and comparing it with predicted movement. The system then adjusts and corrects the tomographic images based on this feedback, resolving the contradiction by continuously improving image quality through iterative correction based on actual observed movement.
2Reliability
If body movement correction is performed after imaging, then image quality can be improved, but it is difficult to appropriately estimate and prevent body movement during imaging
Solution Approach 1:
The system performs preliminary estimation of body movement by acquiring subject information, imaging condition information, and positioning information before imaging. This preliminary action allows the system to predict body movement patterns and prepare appropriate correction strategies, reducing information loss about body movement characteristics.
Solution Approach 2:
The system segments body movement estimation into multiple components: predicted body movement based on pre-acquired information, actual body movement during imaging, and correction amounts for different image regions. This segmentation allows more accurate and comprehensive body movement estimation and correction.
3Adaptability or versatility
If multiple projection images are acquired at different radiation source positions, then tomographic reconstruction is possible, but mechanical errors and body movement cause blur in the reconstructed images
Solution Approach 1:
The system uses feedback by acquiring actual body movement information during the acquisition of multiple projection images and using this information to correct the reconstructed tomographic images. This feedback mechanism maintains adaptability for tomographic imaging while improving image sharpness through motion compensation.
Solution Approach 2:
The system replaces mechanical precision requirements with computational methods by using body movement estimation and correction algorithms. Instead of relying solely on mechanical stability during multi-position imaging, the system uses information processing and mathematical correction to achieve sharp tomographic images despite mechanical variations and body movement.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The apparatus effectively estimates and mitigates body movement, resulting in higher-quality tomographic images with reduced blur, enhancing early detection of breast cancer and other conditions.
Implementation Method 1
a radiation source is moved relative to a detection unit in order to emit radiation to a subject at a plurality of radiation source positions
Data Source
AI summary
An information acquisition unit acquires at least one information item of subject information, imaging condition information, or positioning information. Next, a body movement feature derivation unit derives body movement feature information indicating a feature of body movement of a breast which occurs at the time of the tomosynthesis imaging. A storage stores correspondence information in which the derived body movement feature information corresponds to at least one information item of the subject information, the imaging condition information, or the positioning information.