Patent · US Active

Segmentation and classification of geographic atrophy patterns in patients with age related macular degeneration in widefield autofluorescence images

US12165434B2 · kind B2 · utility

0Cited by

10References

16Claims

0Family size

Assignee

Carl Zeiss Meditec AG · DE

Inventors

Niranchana Manivannan · Fremont, US
Mary K. Durbin · San Jose, US

Key dates

Filing date	Feb 6, 2020
Grant date	Dec 10, 2024
Priority date	—
Expiry date	Apr 18, 2041

Classification

Technology area (CPC G)Physics
CPC primaryG06V2201/03
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

An automated segmentation and identification system/method for identifying geographic atrophy (GA) phenotypic patterns in fundus autofluorescence images. A hybrid process combines a supervised pixel classifier with an active contour algorithm. A trained, machine learning model (e.g., SVM or U-Net) provides initial GA segmentation/classification, and this is followed by Chan-Vese active contour algorithm. The junctional zones of the GA segmented area are then analyzed for geometric regularity and light intensity regularity. A determination of GA phenotype is made, at least in part, from these parameters.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.