Doseless Attenuation Correction in Brain SPECT Imaging
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Solution Overview
Problem
Existing SPECT imaging systems face challenges in attenuation correction, particularly for brain scans, due to the need for CT scans, radiation exposure concerns, and inferior image quality from traditional methods like filtered back projection (FBP), which require manual specification of body boundaries and material mu-values.
Innovation Solution
A doseless attenuation correction method that generates a synthetic mu map by defining a boundary region around the skull in emission tomography images, using either a boundary tracking algorithm or a super ellipse model, to correct for attenuation coefficients, allowing for improved image quality without the need for CT scans or radiation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CT-based attenuation correction is used, then attenuation correction accuracy is improved, but radiation exposure increases and device complexity increases
Solution Approach 1:
The patent creates a synthetic attenuation map (mu-map) that copies the essential attenuation properties of bone and tissue without using actual CT scan data. The method generates a simplified model representing the skull and brain tissue attenuation characteristics, allowing accurate attenuation correction while avoiding the need for ionizing radiation from CT scans
Solution Approach 2:
The patent extracts only the necessary attenuation information from the imaging process by using the emission data itself to define the boundary region and generate the synthetic mu-map. This separates the attenuation correction function from the CT scanning process, eliminating the need for additional radiation exposure while maintaining correction accuracy
2Measurement precision
If CT-based attenuation correction is used, then attenuation correction accuracy is improved, but device complexity increases
Solution Approach 1:
The patent makes the SPECT imaging system itself perform the attenuation correction function that traditionally required a separate CT scanner. By using the emission data to generate both the image and the attenuation map, the system achieves multi-functionality without adding CT scan equipment, thereby reducing device complexity while maintaining correction accuracy
3Device complexity
If FBP with Chang's method is used, then device complexity is reduced, but image quality deteriorates and manual intervention is required
Solution Approach 1:
The patent enables the system to automatically define the boundary region and generate the synthetic mu-map without requiring manual specification of body boundaries or material mu-values. The emission data itself is used to identify the skull boundary and calculate appropriate attenuation coefficients, making the system self-sufficient and eliminating operator intervention while improving image quality through more accurate 3D iterative reconstruction
Solution Approach 2:
The patent transitions from the approximate FBP method to a more accurate 3D iterative reconstruction method. This changes the reconstruction parameters and algorithms used, allowing for precise attenuation correction that accounts for the actual geometry and distribution of attenuating materials, thereby significantly improving image quality
4Device complexity
If FBP with Chang's method is used, then device complexity is reduced, but manual intervention is required
Solution Approach 1:
The patent enables the system to automatically define the boundary region and generate the synthetic mu-map without requiring manual specification of body boundaries or material mu-values. The emission data itself is used to identify the skull boundary and calculate appropriate attenuation coefficients, making the system self-sufficient and eliminating operator intervention
Data Source
AI summary
Systems and methods for generating corrected emission tomography images are provided. A method includes obtaining a reconstructed image based on emission tomography data of a head of a patient and defining a boundary region in the reconstructed image estimating a position of a skull of the patient in the reconstructed image. The method also includes generating a map of attenuation coefficient values for the reconstructed image based on the boundary region. The reconstructed image can then be adjusted based on the map. In the method, the attenuation coefficient values within the boundary region are selected to correspond to an attenuation coefficient value for bone and the attenuation coefficient values for the portion of the image surrounded by the boundary region are selected to correspond to an attenuation value for tissue.