Expanding Dense MRI Applications through Deep Learning-based Phase Unwrapping
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Summary of the Inventive Concept
This inventive concept leverages the core technology of dense MRI using deep learning for phase unwrapping to tackle diverse applications beyond cardiac strain imaging, including crop growth monitoring, soil moisture evaluation, composite material defect detection, fluid dynamics analysis, and biomechanical property monitoring of implantable medical devices.
Background and Problem Solved
The original patent focused on cardiac strain imaging using dense MRI with deep learning-based phase unwrapping. However, this technology has the potential to address various other industries and challenges. The new inventive concept tackles the limitation of the original patent by exploring new applications and use cases, thereby expanding the technology's reach and impact.
Detailed Description of the Inventive Concept
The inventive concept involves adapting the core technology of dense MRI with deep learning-based phase unwrapping to various new applications. In crop growth monitoring, dense MRI can encode displacement information of plant tissues into phase data, which is then unwrapped using a deep learning module. The resulting unwrapped phase data is analyzed to quantify plant growth. Similarly, in soil moisture evaluation, DENSE MRI is used to acquire displacement encoded MRI data of soil samples, which is then analyzed using a deep learning-based phase unwrapping algorithm to determine soil moisture levels. Other applications include detecting defects in composite materials, analyzing fluid dynamics in industrial pipelines, and monitoring biomechanical properties of implantable medical devices.
Novelty and Inventive Step
The new inventive concept introduces novel applications and use cases for dense MRI with deep learning-based phase unwrapping, going beyond cardiac strain imaging. The inventive step lies in recognizing the potential of this technology to address diverse challenges and developing new methods and systems to achieve this.
Alternative Embodiments and Variations
Alternative embodiments may include using different deep learning architectures or optimization techniques for phase unwrapping, or integrating the technology with other imaging modalities. Variations may include applying the technology to other biological tissues or materials, or using it for quality control in manufacturing processes.
Potential Commercial Applications and Market
The new inventive concept has significant commercial potential across various industries, including agriculture, construction, manufacturing, and healthcare. The market for these applications is substantial, with potential customers including farmers, construction companies, manufacturers, and medical device companies.
Original Patent Information
| Patent Number | US 11,857,288 |
|---|---|
| Title | Systems and methods for phase unwrapping for dense MRI using deep learning |
| Assignee(s) | University of Virginia Patent Foundation |