US 12,288,337 B2
Automated assessment of glaucoma loss from optical coherence tomography
Michael Abramoff, University Heights, IA (US); and Milan Sonka, Coralville, IA (US)
Assigned to University of lowa Research Foundation, Iowa City, IA (US); and UNITED STATES GOVERNMENT AS REPRESENTED BY THE DEPARTMENT OF VETERANS AFFAIRS, Washington, DC (US)
Filed by University of Iowa Research Foundation, Iowa City, IA (US)
Filed on Nov. 29, 2023, as Appl. No. 18/522,805.
Application 18/522,805 is a continuation of application No. 16/440,480, filed on Jun. 13, 2019, granted, now 11,972,568.
Application 16/440,480 is a continuation of application No. 15/371,925, filed on Dec. 7, 2016, granted, now 10,354,384, issued on Jul. 16, 2019.
Application 15/371,925 is a continuation of application No. 14/397,756, granted, now 9,545,196, issued on Jan. 17, 2017, previously published as PCT/US2013/032477, filed on Mar. 15, 2013.
Claims priority of provisional application 61/642,945, filed on May 4, 2012.
Prior Publication US 2024/0104741 A1, Mar. 28, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 3/00 (2006.01); A61B 3/10 (2006.01); A61B 3/12 (2006.01); G06T 7/00 (2017.01)
CPC G06T 7/0016 (2013.01) [A61B 3/0025 (2013.01); A61B 3/102 (2013.01); A61B 3/1225 (2013.01); G06T 2207/10101 (2013.01); G06T 2207/30041 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
determining macular damage based on thickness of a cell layer within a retinal image;
determining a set of correlations of the cell layer to each of a plurality of nerve regions within the retinal image;
identifying from the plurality of nerve regions, based on a highest correlation from among the set of correlations, a nerve region that corresponds to the cell layer; and
determining that the nerve region is affected by macular damage.