GEOGRAPHIC ATROPHY IDENTIFICATION AND MEASUREMENT

• US 20150201829A1
• Filed: 12/22/2014
• Published: 07/23/2015
• Est. Priority Date: 01/21/2014
• Status: Active Grant

• Current Assignee: Kabushiki Kaisha Topcon
• Original Assignee: Kabushiki Kaisha Topcon
• Inventors: Yang, Qi, Reisman, Charles A.
• Granted Patent: US 9,526,412 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 3/0025 characterised by electronic signal processing, e.g. eye models
• CPC Class Codes: A61B 3/102 for optical coherence tomography [OCT]
• CPC Class Codes: A61B 3/1025 for confocal scanning
• CPC Class Codes: A61B 3/12 for looking at the eye fundus, e.g. ophthalmoscopes A61B3/13 takes precedence
• CPC Class Codes: A61B 3/1225 using coherent radiation
• CPC Class Codes: A61B 5/4842 Monitoring progression or stage of a disease
• CPC Class Codes: G01B 9/02091 Tomographic interferometers, e.g. based on optical coherence
• CPC Class Codes: G01N 2021/1787 Tomographic, i.e. computerised reconstruction from projective measurements
• CPC Class Codes: G01N 2021/887 the measurements made in two or more directions, angles, positions
• CPC Class Codes: G01N 21/4795 spatially resolved investigating of object in scattering medium in vivo A61B
• CPC Class Codes: G01N 21/6456 Spatial resolved fluorescence measurements; Imaging
• CPC Class Codes: G06T 2207/10101 Optical tomography; Optical coherence tomography [OCT]
• CPC Class Codes: G06T 2207/30041 Eye; Retina; Ophthalmic
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 40/197 Matching; Classification

Abstract

Geographic atrophy of the eye can be detected and measured by imaging the eye at a depth greater than the retinal pigment epithelium (RPE) at a plurality of locations of the eye, for example, using optical coherence tomography (OCT); determining a ratio of the intensities of imaging signals of a retinal layer(s) with respect to the intensity of imaging signals of a sub-RPE layer(s) at each location; determining representative values based at least in part on the determined ratios; generating a map of the representative values; and identifying diseased areas from the map. Contours and binary maps may be generated based on the identified diseased areas. The size and shape of the identified areas may be analyzed and monitored over a period of time.

Claims

1. A method of processing acquired ophthalmic image data comprising:

providing an imaging signal produced by an imaging device capable of penetrating beyond the retinal pigment epithelium (RPE) of a subject'"'"'s eye;

detecting intensities of the imaging signal as the imaging signal is backscattered by each of a plurality of tissue layers in the subject'"'"'s eye for a plurality of axial scans;

determining a ratio of the intensities of the backscattered imaging signals, the ratio being the intensity of the backscattered imaging signal of at least a portion of a retinal layer with respect to the intensity of the backscattered imaging signal of at least a portion of a sub-RPE layer for each of the plurality of axial scans; and

determining a representative value for each of the plurality of axial scans based at least in part on the determined ratio for the corresponding axial scan.

2. The method of claim 1, wherein said at least a portion of a retinal layer comprises a combination of retinal layers, and wherein said at least a portion of a sub-RPE layer comprises a combination of sub-RPE layers.

3. The method of claim 1, wherein the representative value is selected from the group consisting of:

attenuation coefficients, integrated attenuation, or a monotonic or near-monotonic proxy measurement.

4. The method of claim 1, wherein the method further comprises:

identifying diseased areas of the subject'"'"'s eye based at least in part on the determined representative values.

5. The method of claim 4, wherein the step of identifying diseased areas of the subject'"'"'s eye further comprises:

generating a map of the representative values or ratios;

generating seeds of diseased areas;

removing outlier seeds;

growing a region encompassed by the generated seeds that were not removed;

refining a contour of the grown regions;

identifying an area inside the contour as diseased; and

outputting the generated map with a contour around the regions identified as diseased or outputting a binary mask of the regions identified as diseased.

6. The method of claim 5, wherein the step of generating seeds is performed by removing noise from the generated map and applying a thresholding technique on the generated map.

7. The method of claim 6, wherein the thresholding technique comprises finding an Otsu threshold of the generated map, comparing the Otsu threshold with a pre-set value, and selecting an intensity threshold based on the comparison, wherein seeds are generated using pixels of the map that have intensities lower than the selected intensity threshold.

8. The method of claim 5, wherein the step of removing outlier seeds is performed by grouping connected seed components and applying a distance analysis on the generated seeds.

9. The method of claim 1, wherein the imaging signal has a center wavelength of at least 1 μ

m.

10. The method of claim 1, wherein the retinal layer, portion of the retinal layer, combination of retinal layers, sub-RPE layer, portion of a sub-RPE layer, or combination of sub-RPE layers is determined using polarization sensitive optical coherence tomography (PS-OCT).

11. The method of claim 1, wherein the method is used to determine which locations of the subject'"'"'s eyes are diseased;

an area of individual, disease affected regions;

a number of individual, disease affected regions;

a total area of disease affected regions;

a circumference of individual disease affected regions, or a total circumference of disease affected regions.

12. A method of processing acquired ophthalmic image data comprising:

providing an imaging signal produced by an imaging device capable of penetrating beyond the choroid/sclera interface of a subject'"'"'s eye;

detecting intensities of the imaging signal as the imaging signal is backscattered by each of a plurality of tissue layers in the subject'"'"'s eye for a plurality of axial scans;

determining a ratio of the intensities of the backscattered imaging signals for each of the plurality of axial scans, the ratio being the intensity of a first portion of the backscattered imaging signal with respect to the intensity of a second portion of the backscattered imaging; and

determining a representative value of each of the plurality of axial scans based at least in part on the determined ratio for the corresponding axial scan.

13. The method of claim 12, wherein the representative value is selected from the group consisting of:

attenuation coefficients, integrated attenuation, or a monotonic or near-monotonic proxy measurement.

14. The method of claim 12, wherein the method further comprises:

identifying diseased areas of the subject'"'"'s eye based at least in part on the determined representative values.

15. The method of claim 14, wherein the step of identifying diseased areas of the subject'"'"'s eye further comprises:

generating a map of the representative values or ratios;

generating seeds of diseased areas;

removing outlier seeds;

growing a region encompassed by the generated seeds that were not removed;

refining a contour of the grown regions;

identifying an area inside the contour as diseased; and

outputting the generated map with a contour around the regions identified as diseased or outputting a binary mask of the regions identified as diseased.

16. The method of claim 15, wherein the step of generating seeds is performed by removing noise from the generated map and applying a thresholding technique on the generated map.

17. The method of claim 16, wherein the thresholding technique comprises finding an Otsu threshold of the generated map, comparing the Otsu threshold with a pre-set value, and selecting an intensity threshold based on the comparison, wherein seeds are generated using pixels of the map that have intensities lower than the selected intensity threshold.

18. The method of claim 15, wherein the step of removing outlier seeds is performed by grouping connected seed components and applying a distance analysis on the generated seeds.

19. The method of claim 12, wherein the imaging signal has a center wavelength of at least 1 μ

m or is a polarization sensitive optical coherence tomography (PS-OCT) signal.

20. The method of claim 12, wherein the method is used to determine which locations of the subject'"'"'s eyes are diseased;

an area of individual, disease affected regions;

a number of individual, disease affected regions;

a total area of disease affected regions;

a circumference of individual disease affected regions, or a total circumference of disease affected regions.

21. A method of processing acquired ophthalmic image data comprising:

providing an imaging signal produced by a imaging device, the imaging signal having a center wavelength of at least 1 μ

m or being a polarization-sensitive optical coherence tomography (PS-OCT) signal;

detecting intensities of the imaging signal as the imaging signal is backscattered by each of a plurality of tissue layers in a subject'"'"'s eye for a plurality of axial scans;

determining a ratio of the intensities of the backscattered imaging signals for each of the plurality of axial scans, the ratio being the intensity of a first portion of the backscattered imaging signal with respect to the intensity of a second portion of the backscattered imaging;

identifying diseased areas of the subject'"'"'s eye based at least in part on the determined ratio.

22. The method of claim 21, further comprising determining a representative value of each of the plurality of axial scans based at least in part on the determined ratio for the corresponding axial scan, wherein the representative value is selected from the group consisting of:

attenuation coefficients, integrated attenuation, or a monotonic or near-monotonic proxy measurement.

23. The method of claim 22, wherein the step of identifying diseased areas of the subject'"'"'s eye further comprises:

generating a map of the representative values or ratios;

generating seeds of diseased areas;

removing outlier seeds;

growing a region encompassed by the generated seeds that were not removed;

refining a contour of the grown regions;

identifying an area inside the contour as diseased; and

outputting the generated map with a contour around the regions identified as diseased or outputting a binary mask of the regions identified as diseased.

24. The method of claim 23, wherein the step of generating seeds is performed by removing noise from the generated map and applying a thresholding technique on the generated map.

25. The method of claim 24, wherein the thresholding technique comprises finding an Otsu threshold of the generated map, comparing the Otsu threshold with a pre-set value, and selecting an intensity threshold based on the comparison, wherein seeds are generated using pixels of the map that have intensities lower than the selected intensity threshold.

26. The method of claim 23, wherein the step of removing outlier seeds is performed by grouping connected seed components and applying a distance analysis on the generated seeds.

27. The method of claim 21, wherein the method is used to determine which locations of the subject'"'"'s eyes are diseased;

an area of individual, disease affected regions;

a number of individual, disease affected regions;

a total area of disease affected regions;

a circumference of individual disease affected regions, or a total circumference of disease affected regions.