Automated assessment of glaucoma loss from optical coherence tomography
AssigneeUniversity of Iowa Research Foundation
InventorsMichael Abramoff, Milan Sonka
Life of this patent
Estimating the term…
Abstract
Systems and methods for assessing glaucoma loss using optical coherence topography. One method according to an aspect comprises receiving optical coherence image data and assessing functional glaucoma damage from retinal optical coherence image data. In an aspect, the systems and methods can map regions and layers of the eye to determine structural characteristics to compare to functional characteristics.
Claims21
1-13. (canceled)
A method comprising:
- receiving an image;
- determining a thickness of a cell layer within at least one of one or more regions of interest of the image;
- determining, for at least one of the one or more regions of interest, a set of correlations of the cell layer thickness to each of a plurality of nerve regions;
- and
- selecting from the plurality of nerve regions, based on a highest correlation from among the set of correlations, a nerve region indicative of macular damage.
A system comprising:
- a memory having computer-executable instructions encoded thereon;
- and
- at least one processor functionally coupled to the memory and configured, by the computer-executable instructions, to:
- receive an image;
- determine a thickness of a cell layer within at least one of one or more regions of interest of the image;
- determine, for at least one of the one or more regions of interest, a set of correlations of the cell layer thickness to each of a plurality of nerve regions;
- and
- select from the plurality of nerve regions, based on a highest correlation from among the set of correlations, a nerve region indicative of macular damage.
A computer-readable storage medium comprising processor-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to:
- receive a spectral-domain optical coherence tomography (SD-OCT) image;
- determine a thickness of a macular ganglion cell layer (GCL) within at least one of one or more regions of interest of the SD-OCT image;
- determine, for at least one of the one or more regions of interest, a set of correlations of the GCL thickness to each of a plurality of optic nerve head (ONH) regions;
- select from the plurality of ONH regions, based on a highest correlation from among the set of correlations, an ONH region indicative of macular damage;
- determine, for each of a plurality of nerve fiber bundle (NFB) regions within at least one of the one or more areas of interest, a connectivity path of the GCL to at least two nerve fiber bundle (NFB) segments within the NFB region;
- and
- determine, for each NFB region, a path of a retinal ganglion cell-axonal complex (RGC-AC) segment with a highest cumulative correlation among all possible RGC-AC segment paths.
Dependencies are inferred from the claim text.