Iterative X-ray Imaging Optimization for Medical Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current x-ray medical imaging systems, such as spectral mammography and digital breast tomosynthesis, face challenges in accurately correlating data from different image datasets, leading to the need for repeated image acquisitions and increased radiation dosage, especially when refining analysis of regions of interest (ROI).
Innovation Solution
A medical imaging system and method that optimizes acquisition geometry for individual patients by dynamically combining existing image datasets with additional data and contextual information, allowing for enhanced image quality without requiring completely new datasets, thus reducing radiation exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple image datasets are acquired from different angles to provide sufficient tissue information, then the completeness of tissue imaging is improved, but the difficulty of correlating data between datasets increases
Solution Approach 1:
The patent merges multiple image datasets acquired from different angles into a unified three-dimensional volumetric representation. By combining the datasets in a common coordinate system with consistent pixel spacing and orientation, the system enables accurate correlation of anatomical structures across different views while maintaining complete tissue information.
Solution Approach 2:
The patent transitions from two-dimensional planar images to a three-dimensional volumetric dataset. This dimensional change allows simultaneous visualization and correlation of structures from multiple angles within a single unified space, eliminating the need to manually correlate separate 2D datasets while preserving complete anatomical information.
2Measurement precision
If images are re-acquired to refine analysis of regions of interest, then the diagnostic accuracy is improved, but the radiation dosage to tissue increases
Solution Approach 1:
The patent performs preliminary three-dimensional reconstruction and analysis from the initially acquired datasets before additional image acquisitions. By identifying regions of interest and determining optimal additional view parameters in advance, the system refines diagnostic accuracy while minimizing the number of additional radiation exposures required.
Solution Approach 2:
The patent applies local quality enhancement by focusing additional imaging efforts specifically on identified regions of interest rather than re-acquiring complete datasets. The system determines optimal angular positions and field-of-view parameters tailored to each specific ROI, thereby achieving diagnostic refinement with minimal additional radiation dosage.
3Loss of information
If standard mammography views are acquired to provide comprehensive coverage, then the completeness of examination is improved, but the time required for examination increases
Solution Approach 1:
The patent implements dynamic examination protocols that adapt the number and orientation of acquired views based on real-time analysis of the three-dimensional dataset. The system dynamically determines which additional views are necessary to achieve complete examination coverage, eliminating redundant acquisitions and reducing overall examination time while maintaining comprehensive assessment.
4Measurement precision
If iterative analysis and re-acquisition are performed to refine ROI analysis, then the diagnostic precision is improved, but the productivity of the imaging system decreases
Solution Approach 1:
The patent implements an iterative feedback loop where the three-dimensional reconstruction and initial analysis inform subsequent imaging decisions. The system automatically identifies regions requiring further evaluation, determines optimal additional view parameters, and guides targeted re-acquisitions. This feedback-driven approach refines diagnostic precision while minimizing unnecessary repetitions and maintaining high system productivity.
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
This approach enables highly accurate and optimized representation of ROI in 2D or 3D images, reducing the need for separate image acquisitions and minimizing radiation dosage, while enhancing image quality through iterative analysis and data integration.
Implementation Method 1
an x-ray source (14) that projects an x-ray beam (16)
Data Source
Figure 1
Figure 2
Figure 3
AI summary
In the present invention, a method of optimizing images of a patient utilizing a medical imaging device includes the steps of providing a medical imaging device 10 having an x-ray source 14, an x-ray detector 18, a controller 32 for adjusting the positions of the x-ray source 14 and detector 18, an image reconstructor/generator 38 connected to the x-ray detector to receive x-ray data and reconstruct an x-ray image, and a processor 40 connected to the image reconstructor/generator 38 and the controller 32 and configured to perform analyses on the x-ray image, acquiring a first data set S1 of images, processing the first data set S1 to reconstruct a first computerized data set D1, analyzing the first computerized data set D1, acquiring at least one additional data set Sn in response to the analysis of the first computerized data set D1and processing the at least one additional data set Sn in combination with the first data set S1 to reconstruct an optimized and updated computerized data set Dn.