Tomosynthesis Gain Calibration via High-Low Dose Map Decomposition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional mammography techniques face limitations due to overlapping tissue layers, leading to unclear results, false alarms, and potential missed cancerous growths. Digital breast tomosynthesis improves this by creating 3D images, but it requires effective gain calibration across various imaging parameters to maintain image quality.
Innovation Solution
The method involves performing tomosynthesis sweeps to acquire images at multiple parameters, generating high-dose and low-dose gain maps, decomposing these maps into component levels, and combining high-dose and low-resolution components to create final gain maps for each parameter, thereby reducing the need for high x-ray dose exposures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-dose x-ray images are used for gain calibration, then image quality and noise reduction are improved, but radiation dose to the patient increases
Solution Approach 1:
The gain calibration process is segmented into multiple components: a high-dose reference image is separated from the low-dose tomosynthesis images. The high-dose reference image is used to generate a high-dose gain map, while low-dose gain maps are generated from individual tomosynthesis images. These are then combined through decomposition and reconstruction to create final gain maps that maintain calibration accuracy while using lower radiation doses.
Solution Approach 2:
A high-dose reference image is acquired beforehand to establish a baseline for gain calibration. This preliminary high-dose image enables the system to generate accurate gain maps without requiring all subsequent calibration images to be high-dose, thereby reducing overall radiation exposure while maintaining calibration precision.
2Measurement precision
If multiple tomosynthesis sweeps at different imaging parameters are performed, then gain calibration accuracy across parameters is improved, but imaging time and complexity increase
Solution Approach 1:
The low-dose tomosynthesis images serve multiple functions: they provide the basis for generating low-dose gain maps, and their data is combined with high-dose reference images to create final gain maps. This multi-functionality allows the system to achieve accurate gain calibration across multiple imaging parameters without requiring separate dedicated calibration sweeps for each parameter, thereby reducing total imaging time.
Solution Approach 2:
The system merges high-dose reference images with low-dose tomosynthesis images through a decomposition and reconstruction process. The high-dose reference image provides a baseline gain map that is decomposed into components, which are then combined with low-dose gain maps to produce final gain maps. This merging approach enables accurate multi-parameter calibration while reducing the total number of images required and thus imaging time.
3Object-affected harmful factors
If low-dose images are used for gain calibration, then radiation dose is reduced, but image noise increases
Solution Approach 1:
The final gain maps are created as composite structures by combining high-dose and low-dose image data. The high-dose reference image provides a noise-free baseline that is decomposed into components, which are then combined with low-dose gain maps. This composite approach allows the system to leverage the low noise characteristics of high-dose images while using low-dose images for calibration, thereby reducing overall radiation dose while maintaining image quality.
Solution Approach 2:
The high-dose reference image acts as an intermediary that enables the creation of accurate gain maps from low-dose tomosynthesis images. By using the high-dose reference image to generate a baseline gain map that is then combined with low-dose gain maps through decomposition and reconstruction, the system can achieve accurate calibration without requiring all calibration images to be high-dose, thus reducing radiation dose while maintaining image quality.
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 enhances image quality by reducing noise and maintaining flatness in gain-corrected images, while minimizing the requirement for high x-ray doses, thus improving the efficiency and accuracy of breast tomosynthesis imaging.
Implementation Method 1
an x-ray source and an x-ray image receptor, wherein the image acquisition unit acquires projection x-ray images of an object
Data Source
AI summary
The present application discloses a tomosynthesis system and method that combines high dose gain maps directly, or high-resolution components of high dose gain maps, with low resolution components of low dose gain maps at a plurality of imaging parameters, to produce high quality gain map efficiently at the plurality of imaging parameters, to perform gain corrections to x-ray images.