Seattle, WA, United States of America

Qi Song

This inventor holds 53 USPTO granted patents and 15 published patent applications, primarily in Medical Image Analysis. Top assignees: Shenzhen Keya Medical Technology Corporation, Beijing Keya Medical Technology Co., Ltd., Keya Medical Technology Co., Ltd.. Active years: 2019-2025.

USPTO Granted Patents = 53 

% Patents Active = 92.5

Average Co-Inventor Count = 6.0

ph-index = 12

Forward Citations = 257(Granted Patents)

Forward Citations (Not Self Cited) = 161(Dec 10, 2025)


Company Filing History:


Years Active: 2019-2025

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Areas of Expertise:
Clinical Data Classification
Calcium Scoring
Anatomical Structure Quantification
Image Segmentation
Deep Learning
3D Image Reconstruction
Vascular Image Analysis
COVID-19 Diagnosis
Neural Network
Physiological Condition Detection
Abnormality Detection
Diagnosis Report Generation
53 patents (USPTO):Explore Patents

Title: Innovations by Qi Song in Medical Technology

Introduction: Qi Song is a notable inventor based in Seattle, Washington, with an impressive portfolio consisting of 51 patents. His work focuses on advancing medical technology, particularly methods for disease quantification and anatomical labeling in medical imaging.

Latest Patents: Qi Song's latest patents showcase his commitment to improving medical diagnostics.

1. **Method and System for Disease Quantification of Anatomical Structures**: This patent introduces a method for predicting disease quantification parameters for anatomical structures. The process involves extracting a centerline structure from medical images and employing a Graph Neural Network (GNN) to predict parameters at various sampling points along the centerline. By integrating local and global factors, this method aims to enhance prediction accuracy significantly.

2. **Method and System for Anatomical Labels Generation**: In this innovation, Qi has developed a system for automatically generating anatomical labels from medical images. Utilizing a deep learning network that incorporates various advanced techniques, including branched networks and probabilistic models, this method ensures high accuracy and reliability in labeling anatomical structures.

Career Highlights: Qi has made remarkable contributions during his tenure at Shenzhen Keya Medical Technology Corporation and Keya Medical Technology Co., Ltd. His work has not only advanced the field of medical imaging but also paved the way for more effective disease diagnosis and treatment methodologies.

Collaborations: Throughout his career, Qi has collaborated with esteemed colleagues including Youbing Yin and Junjie Bai. Their combined expertise enhances the innovative capabilities of their projects, leading to noteworthy advancements in medical technology.

Conclusion: Qi Song's contributions to medical technology are significant, with a strong focus on improving diagnostic methods through innovative patent developments. His latest work exemplifies the intersection of advanced technology and healthcare, promising better outcomes in disease detection and anatomical understanding.

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