This inventor holds 2 USPTO granted patents and 1 published patent application and 1 EPO patent. Top assignee: Allen Institute. Active years: 2022-2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2022-2025
Title: Innovations of Jianxu Chen in 3D Microscopy
Introduction
Jianxu Chen is an accomplished inventor based in Shoreline, WA (US). He has made significant contributions to the field of microscopy through his innovative patent. His work focuses on enhancing the identification of 3D intracellular structures, which is crucial for various scientific and medical applications.
Latest Patents
Jianxu Chen holds a patent titled "Segmenting 3D intracellular structures in microscopy images using an iterative deep learning workflow that incorporates human contributions." This patent describes a facility designed to identify the boundaries of 3-dimensional structures in 3-dimensional images. The facility receives initial results from attempts to identify these boundaries and presents them to a person for feedback. This feedback is then utilized to train a deep-learning network, improving the accuracy of boundary identification in subsequent images. Jianxu Chen has 1 patent to his name.
Career Highlights
Jianxu Chen is currently employed at the Allen Institute, where he continues to push the boundaries of research in microscopy. His work is instrumental in advancing the understanding of complex biological structures, which can lead to breakthroughs in various fields, including medicine and biology.
Collaborations
Jianxu Chen collaborates with talented colleagues such as Liya Ding and Matheus Palhares Viana. Their combined expertise fosters an environment of innovation and discovery, contributing to the success of their projects.
Conclusion
Jianxu Chen's innovative work in microscopy exemplifies the impact of deep learning on scientific research. His contributions are paving the way for more accurate and efficient methods of analyzing 3D structures, which is essential for future advancements in the field.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile