Joint-Visualization Image Generation for Functional Imaging Data
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Solution Overview
Problem
Conventional techniques struggle to achieve satisfactory visual clarity when overlaying or blending different functional imaging data types in a single fused image, often resulting in visual confusion and undesired hues/colors.
Innovation Solution
A method and workstation for functional imaging that involves accessing multiple functional imaging datasets, registering them, determining a visualization priority for each pixel based on logical comparisons, and generating a joint-visualization image that represents information from multiple data types simultaneously.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple functional imaging data types are overlayed or blended in a single fused image, then comprehensive information representation is achieved, but visual clarity deteriorates resulting in visual confusion and undesired hues/colors
Solution Approach 1:
The patent segments the visualization task by creating separate visualization layers for different functional imaging data types (PET, SPECT, fMRI) rather than blending them into a single fused image. Each layer maintains its own visual characteristics and color mapping, preventing visual confusion while preserving comprehensive information representation through layered composition.
Solution Approach 2:
The patent transitions from a two-dimensional blended image approach to a multi-dimensional layered visualization structure. By organizing data types into separate layers that can be independently controlled and positioned, the system achieves both complete information representation and maintained visual clarity through spatial separation in the visualization dimension.
2Loss of information
If multiple functional imaging data types are combined in a single image, then diagnostic information is comprehensive, but image interpretability decreases due to visual confusion
Solution Approach 1:
The patent divides the imaging data into separate functional layers (PET layer, SPECT layer, fMRI layer), each with distinct visual properties and color mappings. This segmentation allows clinicians to interpret each data type independently without confusion from overlapping visual information, while still accessing comprehensive diagnostic data through the layered structure.
Solution Approach 2:
The patent applies different visualization qualities and characteristics to different regions and data types within the same image framework. Each functional imaging data type maintains its own optimized visual properties (color maps, contrast, transparency) tailored to its specific diagnostic requirements, enhancing overall interpretability while preserving information completeness.
Data Source
AI summary
A method and workstation for combining multiple functional imaging datasets into a joint-visualization image. In one aspect, a method of functional imaging includes accessing a plurality of functional imaging datasets acquired from a volume-of-interest, wherein each of the plurality of functional imaging datasets is a different one of a plurality of functional imaging data types. The method includes registering the plurality of functional imaging datasets and determining a visualization priority for each of a plurality of pixels in a joint-visualization image based on a logical comparison of corresponding information in each of the plurality of functional imaging datasets. The method includes generating the joint-visualization image based on the visualization priority and at least a portion of each of the plurality of functional imaging datasets, wherein each of a plurality of pixels in the joint-visualization image represents only a single one of the plurality of functional imaging data types.