New York, NY, United States of America

Yan Wen

USPTO Granted Patents = 3 

Average Co-Inventor Count = 6.2

ph-index = 1

Forward Citations = 6(Granted Patents)


Company Filing History:


Years Active: 2021-2025

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3 patents (USPTO):Explore Patents

Title: The Innovations of Inventor Yan Wen in Quantitative Susceptibility Mapping

Introduction: Yan Wen is a distinguished inventor based in New York, NY, who has made significant contributions to the field of magnetic resonance imaging (MRI). With two patents to his name, he has demonstrated an exceptional ability to innovate in complex imaging technologies.

Latest Patents: Yan Wen's latest patents focus on advanced systems and methods for robust quantitative susceptibility mapping. These innovative approaches utilize Bayesian inference to generate images of tissue magnetism properties from complex MRI data. The patent outlines a robust framework that minimizes a specially constructed cost function, incorporating data fidelity and regularization terms. By directly utilizing complex MRI data, his methods construct prior information from known morphology and homogenous susceptibility regions, enabling accurate determination of magnetic susceptibility information associated with various structures.

Career Highlights: Currently, Yan Wen is affiliated with Cornell University, where he engages in cutting-edge research and development in imaging technologies. His expertise in quantitative susceptibility mapping places him at the forefront of advancements in MRI technology, fostering a deeper understanding of tissue properties.

Collaborations: Yan Wen has collaborated with esteemed colleagues, including Yi Jing Wang and Zhe Liu. These partnerships have enriched his research endeavors, allowing for a multi-disciplinary approach to solving complex problems related to magnetic resonance imaging.

Conclusion: Yan Wen's innovative work in the field of quantitative susceptibility mapping exemplifies the transformative potential of advanced imaging technologies. His contributions are poised to enhance diagnostic capabilities and improve clinical outcomes in medical imaging.

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