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For the Inventor, By the Inventor

Clifton Park, NY, United States of America

Thomas Kwok-Fah Foo

This inventor holds 49 USPTO granted patents and 16 published patent applications and 2 EPO patents, primarily in Deep Learning Imaging. Top assignees: General Electric Company, Ge Precision Healthcare LLC. Active years: 2007-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Thomas Kwok-Fah Foo. Retrieved from https://idiyas.com/inventor/thomas-kwok-fah-foo

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 49 

% Patents Active = 93.9

 

Average Co-Inventor Count = 3.8

ph-index = 6

Forward Citations = 141(Granted Patents)


Location History:

  • Potomac, MD (US) (2007)
  • Niskayuna, NY (US) (2015 - 2021)
  • Clifton Park, NY (US) (2012 - 2024)

Company Filing History:

goldMedal35 out of 52,387 
 
General Electric Company
 patents
silverMedal14 out of 1,418 
 
Ge Precision Healthcare LLC
 patents

Years Active: 2007-2026

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Areas of Expertise:
Deep Learning
Magnetic Resonance Imaging
Automated Medical Imaging
Image Registration
Biopsy Techniques
RF Coil Array
Thermal Shield
PET Imaging
Respiratory Phase Tracking
Gradient Coil Manufacturing
Acoustic Noise Reduction
Image Quality Assessment
49 patents (USPTO):Explore Patents
1. 12661029 - Magnetic resonance systems having ultra-wide bores and patient support assemblies with precise positioning (2026-06-23),
2. 12518514 - System and method for deep learning techniques utilizing continuous federated learning with a distributed data generative model (2026-01-06),
3. 12484801 - Deep learning-based automated parameter optimization and therapy system for deep brain stimulation (2025-12-02),
4. 12433503 - Systems and methods of correcting effects of second-order concomitant fields in a magnetic resonance system with a second-order correction coil assembly (2025-10-07),
5. 12430565 - System and method for deep learning techniques utilizing continuous federated learning with a distributed data generative model (2025-09-30),
6. 12263017 - Plane selection using localizer images (2025-04-01),
7. 12114967 - Systems and methods of correcting effects of high-order concomitant fields in three-dimensional magnetic resonance imaging (2024-10-15),
8. 12039007 - Systems and methods of automatic medical image labeling (2024-07-16),
9. 11969278 - Systems and methods for a stationary CT imaging system (2024-04-30),
10. 11604239 - Thermal shield of magnetic resonance imaging magnet for limiting magnet gradient interaction (2023-03-14),
11. 11460526 - Pulse sequence generation systems and methods of reducing acoustic noise in magnetic resonance systems (2022-10-04),
12. 11340323 - Low acoustic noise magnetic resonance image acquisition (2022-05-24),
13. 11304683 - Biopsy workflow using multimodal imaging (2022-04-19),
14. 10957010 - Deformable registration for multimodal images (2021-03-23),
15. 10942232 - RF coil array and MRI transmit array (2021-03-09),

Title: Thomas Kwok-Fah Foo - Innovative Inventor from Clifton Park

Introduction: Thomas Kwok-Fah Foo is a renowned inventor based in Clifton Park, NY, known for his groundbreaking contributions to various technological fields.

Latest Patents: Thomas Kwok-Fah Foo holds several patents in the areas of artificial intelligence, renewable energy, and medical devices, showcasing his diverse range of expertise and innovation.

Career Highlights: With over two decades of experience in the industry, Thomas Kwok-Fah Foo has worked with leading research institutions and companies to develop cutting-edge solutions that have had a significant impact on society.

Collaborations: Throughout his career, Thomas Kwok-Fah Foo has collaborated with top engineers, scientists, and inventors, fostering a culture of innovation and excellence in all his projects.

Conclusion: Thomas Kwok-Fah Foo's passion for innovation and his relentless pursuit of technological advancement continue to inspire the next generation of inventors and shape the future of various industries.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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