PET Scanner Image Reconstruction Segmentation for Lesion Quantitation
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Solution Overview
Problem
Existing imaging systems, such as PET scanners, face challenges in optimizing image reconstruction algorithms for both quantitation accuracy and visual image quality, often resulting in unnatural image appearances and increased false positives due to the trade-off between these objectives.
Innovation Solution
A method and system that separately reconstructs display and quantitation images using distinct algorithms optimized for each objective, with the quantitation algorithm tailored to optimize lesion quantitation figures of merit by determining penalty function types and parameter values based on scanner geometry, data acquisition protocols, and lesion characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single image reconstruction algorithm is used for both quantitation and display, then the system complexity is reduced, but the quantitation accuracy and visual image quality cannot be simultaneously optimized
Solution Approach 1:
The patent divides the image reconstruction process into two separate algorithms: one optimized for quantitation accuracy and another optimized for visual display quality. This segmentation allows each algorithm to be independently tuned for its specific purpose, resolving the contradiction between system simplicity and quantitation precision.
2Measurement precision
If an image reconstruction algorithm is optimized for quantitation accuracy, then measurement precision is improved, but visual image quality deteriorates with unnatural appearance and increased false positives
Solution Approach 1:
The patent separates the quantitation reconstruction algorithm from the display reconstruction algorithm, allowing the quantitation algorithm to focus solely on measurement precision without compromising detection reliability. The display algorithm can then be optimized for natural appearance and false positive reduction.
Solution Approach 2:
The patent applies different quality characteristics to different aspects of the imaging system: high precision and accuracy to the quantitation image, and high visual quality and natural appearance to the display image. This local optimization resolves the contradiction between measurement precision and detection reliability.
3Ease of operation
If a single image reconstruction algorithm is used for display purposes, then ease of operation is maintained, but quantitation accuracy suffers from suboptimal reconstruction
Solution Approach 1:
The patent implements a segmented reconstruction approach where the quantitation-optimized algorithm operates independently to generate accurate measurement data, while the display-optimized algorithm handles visual presentation. This maintains operational simplicity while achieving high quantitation accuracy.
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 improves diagnostic capability by enhancing both quantitation accuracy and visual image quality, allowing for precise lesion detection and measurement while minimizing false positives.
Implementation Method 1
The scintillator crystals receive the annihilation photons and generate light photons in response to the annihilation photons
Implementation Method 2
the light photons emitted to a photosensor configured to convert the light energy from the light photons to electrical energy used to reconstruct an image
Data Source
AI summary
A method includes acquiring scan data for an object to be imaged using an imaging scanner. The method also includes reconstructing a display image using the scan data. Further, the method includes determining one or more aspects of a quantitation imaging algorithm for generating a quantitation image, wherein the one or more aspects of the quantitation imaging algorithm are selected to optimize a quantitation figure of merit for lesion quantitation. The method also includes reconstructing a quantitation image using the scan data and the quantitation imaging algorithm; displaying, on a display device, the display image; determining a region of interest in the display image; determining, for the region of interest, a lesion quantitation value using a corresponding region of interest of the quantitation image; and displaying, on the display device, the lesion quantitation value.