Menlo Park, CA, United States of America

Leandra L Brickson

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Leland Stanford Junior University. Active years: 2021.

USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2021

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1 patent (USPTO):Explore Patents

Title: Leandra L Brickson: Innovator in Ultrasound Imaging Technology

Introduction

Leandra L Brickson is a prominent inventor based in Menlo Park, CA (US). She has made significant contributions to the field of ultrasound imaging technology. Her innovative work focuses on enhancing the quality of ultrasound images through advanced techniques.

Latest Patents

Leandra holds a patent for "Ultrasound speckle reduction and image reconstruction using deep learning techniques." This patent involves reconstructing ultrasound B-mode images directly from transducer channel signals using a convolutional neural network (CNN). The CNN is trained with a dataset that includes simulated transducer array channel signals containing simulated speckle, with corresponding simulated speckle-free B-mode ground truth images as outputs. After training, real-time RF signals taken directly from an ultrasound transducer array are input to the CNN, which processes them to generate an estimated real-time B-mode image with reduced speckle. Leandra has 1 patent to her name.

Career Highlights

Leandra is affiliated with Leland Stanford Junior University, where she continues to push the boundaries of ultrasound technology. Her work has garnered attention for its potential to improve diagnostic imaging and patient outcomes.

Collaborations

Leandra collaborates with talented individuals in her field, including Dongwoon Hyun and Kevin T Looby. Their combined expertise contributes to the advancement of ultrasound imaging techniques.

Conclusion

Leandra L Brickson is a trailblazer in the field of ultrasound imaging, with her innovative patent showcasing the power of deep learning in medical technology. Her contributions are paving the way for improved imaging techniques that can significantly benefit healthcare.

Profile summary based on public USPTO records.
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