Yuankai Huo

Title: Innovations by Yuankai Huo

Introduction

Yuankai Huo is a notable inventor based in Bethesda, MD (US). He has made significant contributions to the field of medical imaging and pathology through his innovative patents. With a total of 4 patents, Huo's work focuses on enhancing the accuracy and efficiency of lesion annotation and segmentation in clinical images.

Latest Patents

Huo's latest patents include a method and system for harvesting lesion annotations. This method involves conditioning a lesion proposal generator (LPG) based on a first two-dimensional (2D) image set. The process includes adding lesion annotations to the first 2D image set to create a revised version, forming a three-dimensional (3D) composite image, and reducing false-positive lesion annotations. The conditioned LPG is then applied to a second 2D image set to harvest lesion annotations effectively.

Another significant patent is related to co-heterogeneous and adaptive 3D pathological abdominal organ segmentation. This computer-implemented method processes clinical three-dimensional images by training a fully supervised segmentation model using a labeled image dataset. The model is further refined through co-heterogeneous training and adversarial domain adaptation, allowing it to segment images across various contrast phases or modalities.

Career Highlights

Yuankai Huo is currently employed at Ping An Technology (Shenzhen) Co., Ltd. His work at this company has allowed him to collaborate with other talented professionals in the field. His innovative approaches have contributed to advancements in medical imaging technology.

Collaborations

Some of Huo's notable coworkers include Adam Patrick Harrison and Jinzheng Cai. Their collaborative efforts have further enhanced the research and development of medical imaging solutions.

Conclusion

Yuankai Huo's contributions to the field of medical imaging through his patents demonstrate his commitment to innovation and improvement in clinical practices. His work continues to influence the way medical professionals analyze and interpret imaging data.