Location History:
- Atlanta, GA (US) (2014)
- Santa Clara, CA (US) (2021)
Company Filing History:
Years Active: 2014-2021
Title: Innovations by Yu-Ying Liu
Introduction
Yu-Ying Liu is a notable inventor based in Santa Clara, California. He has made significant contributions to the field of medical technology, particularly in disease progression modeling and optical coherence tomography.
Latest Patents
Yu-Ying Liu holds two patents that showcase his innovative work. The first patent, titled "Systems and methods for disease progression modeling," describes a method for determining a disease state transition path. This method involves receiving patient data that includes functional and/or structural data. Based on this data, a first disease state is identified, and a second, non-adjacent disease state is determined. A most probable path between these states is established using a two-dimensional continuous-time hidden Markov model. The second patent, "Automated macular pathology diagnosis in three-dimensional (3D) spectral domain optical coherence tomography (SD-OCT) images," discusses systems and methods for analyzing optical coherence tomography images of the retina. This patent details how a 2-dimensional slice of the image can be aligned to produce an approximately horizontal image of the retina, along with an edge map based on the aligned slice.
Career Highlights
Throughout his career, Yu-Ying Liu has worked with prestigious institutions such as the University of Pittsburgh and Georgia Tech Research Corporation. His work has significantly advanced the understanding and diagnosis of ocular pathologies.
Collaborations
Yu-Ying Liu has collaborated with notable professionals in his field, including Hiroshi Ishikawa and Gadi Wollstein. These collaborations have further enriched his research and innovations.
Conclusion
Yu-Ying Liu's contributions to medical technology through his patents and collaborations highlight his role as an influential inventor. His work continues to impact the field of disease diagnosis and progression modeling.