Jaime Levy

Title: Jaime Levy: Advancing Retinal Atrophy Classification with Machine Learning

Introduction

Jaime Levy is an inventor associated with Bet Shemesh, Israel. Her patent work focuses on applying machine learning to optical coherence tomography (OCT) scans to help classify retinal atrophy.

Latest Patents

Levy is named on one patent, titled “Machine learning classification of retinal atrophy in OCT scans.” The method receives OCT scans taken at different times, along with associated retinal images, and matches corresponding pixel-column patches between the scans using image registration. A trained machine-learning model then uses the matched patches to classify whether the later scan’s patches represent retinal atrophy. This approach is designed to support the analysis of changes in retinal scans over time.

Career Highlights

Levy’s listed patent activity centers on medical imaging and machine-learning classification. Her contribution is reflected in 1 patent.

Collaborations

Levy’s listed coworkers include Leo Joskowicz and Adi Szeskin, who are associated with the patent work.

Conclusion

Jaime Levy’s patent describes a machine-learning approach for comparing OCT scans and classifying retinal atrophy, highlighting the potential of computational methods in retinal imaging.