Los Angeles, CA, United States of America

Yilin Luo

USPTO Granted Patents = 1 

Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Yilin Luo: Innovator in Digital Staining Technologies

Introduction

Yilin Luo is a prominent inventor based in Los Angeles, CA, known for her groundbreaking work in the field of microscopy. She has made significant contributions to the development of digital staining methods that leverage deep learning technologies. Her innovative approach has the potential to revolutionize how microscopic images are analyzed and interpreted.

Latest Patents

Yilin Luo holds a patent for a "Method and system for digital staining of microscopy images using deep learning." This patent describes a deep learning-based digital staining method that enables the creation of digitally stained microscopic images from label-free or unstained samples. The method utilizes fluorescence lifetime images obtained from a fluorescence microscope to generate virtually stained images. Additionally, it includes a digital autofocusing method that employs machine learning to enhance image focus using a trained deep neural network. This technology allows for the generation of stained images that closely resemble those obtained through traditional histochemical staining methods.

Career Highlights

Yilin Luo is affiliated with the University of California, where she continues to advance her research in microscopy and imaging technologies. Her work has garnered attention for its innovative use of deep learning in the field, showcasing her commitment to pushing the boundaries of scientific research.

Collaborations

Yilin has collaborated with notable researchers such as Aydogan Ozcan and Yair Rivenson, contributing to the advancement of digital imaging technologies. These collaborations have further enhanced her research and expanded the impact of her innovations.

Conclusion

Yilin Luo's contributions to digital staining technologies represent a significant advancement in microscopy. Her innovative methods have the potential to improve the accuracy and efficiency of microscopic image analysis, paving the way for future developments in the field.

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