Oakland, CA, United States of America

King Chung Ho

This inventor holds 2 USPTO granted patents and 1 published patent application. Top assignee: University of California. Active years: 2021-2023.

USPTO Granted Patents = 2 

% Patents Active = 50.0

Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2021-2023

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2 patents (USPTO):Explore Patents

Title: King Chung Ho: Innovator in Medical Imaging Technology

Introduction

King Chung Ho is a prominent inventor based in Oakland, CA (US). He has made significant contributions to the field of medical imaging, particularly through his innovative use of deep neural networks. With a total of 2 patents, his work is paving the way for advancements in healthcare technology.

Latest Patents

King Chung Ho's latest patents focus on systems and methods for analyzing perfusion-weighted medical imaging using deep neural networks. These patents describe a method that includes receiving perfusion-weighted imaging data acquired from a subject using a magnetic resonance (MR) imaging system. The process involves modeling at least one voxel associated with the imaging data using a four-dimensional (4D) convolutional neural network. Additionally, the method extracts spatio-temporal features for each modeled voxel and estimates at least one perfusion parameter based on these features. Ultimately, the method generates a report indicating perfusion in the subject.

Career Highlights

King Chung Ho is affiliated with the University of California, where he continues to push the boundaries of medical imaging technology. His work has garnered attention for its potential to improve diagnostic accuracy and patient outcomes.

Collaborations

Some of his notable coworkers include Corey W Arnold and Fabien Scalzo, who contribute to the collaborative efforts in advancing medical imaging research.

Conclusion

King Chung Ho's innovative work in medical imaging exemplifies the impact of technology on healthcare. His patents reflect a commitment to enhancing diagnostic methods through advanced neural network applications.

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