Wuhan, China

Fengli He

This inventor holds 2 USPTO granted patents. Top assignee: Shanghai United Imaging Healthcare Co., Ltd.. Active years: 2021-2023.


% Patents Active = 100.0

Average Co-Inventor Count = 11.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2021-2023

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2 patents (USPTO):Explore Patents

Title: Innovations by Fengli He in Image Segmentation

Introduction

Fengli He is an accomplished inventor based in Wuhan, China. He has made significant contributions to the field of medical imaging, particularly in the area of image segmentation. With a total of 2 patents, his work focuses on enhancing the analysis of lung images, which is crucial for medical diagnostics.

Latest Patents

Fengli He's latest patents include innovative methods and systems for image segmentation. One of his notable applications discloses a method for segmenting a lung image. This method involves obtaining a target image related to a lung region, which may consist of multiple image slices. The process includes segmenting the lung region from the target image, identifying airway structures, and recognizing one or more fissures within the lung region. Additionally, the method determines one or more pulmonary lobes in the lung region, showcasing its potential for improving diagnostic accuracy.

Career Highlights

Fengli He is currently associated with Shanghai United Imaging Healthcare Co., Ltd., where he continues to develop cutting-edge technologies in medical imaging. His expertise in image segmentation has positioned him as a key player in the healthcare technology sector.

Collaborations

Fengli He collaborates with talented professionals in his field, including Renchao Jin and Lijun Xu. These collaborations enhance the innovation process and contribute to the advancement of medical imaging technologies.

Conclusion

Fengli He is a notable inventor whose work in image segmentation is paving the way for advancements in medical diagnostics. His contributions are vital for improving the accuracy and efficiency of lung image analysis.

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