Hong Kong, China

Hao Du

USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations in Medical Imaging by Hao Du

Introduction

Hao Du is a prominent inventor based in Hong Kong, CN. He has made significant contributions to the field of medical imaging, particularly through his innovative approaches to image segmentation. His work focuses on enhancing the accuracy and effectiveness of medical image analysis, which is crucial for improving patient outcomes.

Latest Patents

Hao Du holds a patent for a groundbreaking invention titled "Weakly-supervised 3D medical image segmentation using geometric prior and contrastive similarity." This patent presents a weakly-supervised framework designed for segmenting three-dimensional (3D) medical images. The framework incorporates geometric prior and contrastive similarity in a loss-based manner to enhance the distinguishability of organs, especially in the presence of complex shapes and image artifacts, such as low-contrast tissues. The training process utilizes images with bounding-box annotations, and the geometric prior is constructed using point-cloud representations, which offer more detailed and flexible supervision compared to traditional volume representations. Additionally, the use of contrastive similarity helps organ pixels cluster effectively in a contrastive embedding space, improving the distinction of low-contrast tissues from the background.

Career Highlights

Hao Du is affiliated with the City University of Hong Kong, where he continues to advance his research in medical imaging technologies. His work has garnered attention for its innovative approach and practical applications in the medical field.

Collaborations

Hao Du collaborates with Jing Liao, contributing to the development of advanced methodologies in medical image analysis.

Conclusion

Hao Du's contributions to medical imaging through his innovative patent demonstrate the potential for technology to enhance healthcare. His work is paving the way for more effective medical image segmentation techniques, ultimately benefiting patient care.

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