Quantifying a blood vessel reflection parameter of the retina

Patent metadata

Field	Value
Publication number	US-2016166141-A1
Application number	US-201414903751-A
Country	US
Kind code	A1
Filing date	Jul 10, 2014
Priority date	Jul 10, 2013
Publication date	Jun 16, 2016
Grant date	—

Abstract

A method for quantifying a blood vessel reflection parameter associated with a biological subject, the method including, in at least one electronic processing device determining, from a fundus image of an eye of the subject, edge points of at least one blood vessel in a region near an optic disc, processing the fundus image, at least in part using the edge points, to identify blood vessel edges and central reflex edges, determining blood vessel and central reflex parameter values using the blood vessel edges and determining a blood vessel reflection parameter value at least partially indicative of blood vessel reflection using the blood vessel and central reflex parameter values.

First claim

1 ) A method for quantifying a blood vessel reflection parameter associated with a biological subject, the method including, in at least one electronic processing device:
a) determining, from a fundus image of an eye of the subject, edge points of at least one blood vessel in a region near an optic disc; b) processing the fundus image, at least in part using the edge points, to identify blood vessel edges and central reflex edges; c) determining blood vessel and central reflex parameter values using the blood vessel edges; and, d) determining a blood vessel reflection parameter value at least partially indicative of blood vessel reflection using the blood vessel and central reflex parameter values.

2 ) The method according to claim 1 , wherein the blood vessel and central reflex parameter values are indicative of blood vessel and central reflex diameters respectively.

3 ) The method according to claim 1 , wherein the blood vessel reflection parameter is based on a ratio of the blood vessel and central reflex parameters.

4 ) The method according to claim 1 , wherein the region is an annular region surrounding the optic disc.

5 ) The method according to claim 1 , wherein the method further includes:
determining an optic disc location; determining an extent of the optic disc at least in part using the optic disc location; and, determining the region using the extent of the optic disc.

6 ) The method according to claim 5 , wherein the method further includes determining the optic disc location by:
displaying the at least one fundus image to a user; and, determining the optic disc location in accordance with user input commands.

7 ) The method according to claim 1 , wherein the method further includes:
displaying an indication of the region to the user; and, determining the edge points in accordance with user input commands.

8 ) The method according to claim 1 , wherein the method includes processing the fundus image by:
rotating the fundus image so that the blood vessel extends substantially across the fundus image; and, cropping the fundus image to remove parts of the fundus image beyond an extent of the edge points.

9 ) The method according to claim 1 , wherein the method further includes:
identifying potential edges in the fundus image using an edge detection algorithm; selecting edges from the potential edges using an edge selection algorithm.

10 ) The method according to claim 1 , wherein the method further includes:
identifying outer edges as blood vessel edges; and, determining edges between the blood vessel edges to be potential central reflex edges.

11 ) The method according to claim 10 , wherein the method further includes selecting central reflex edges from the potential central reflex edges based on changes in image intensity.

12 ) The method according to claim 1 , wherein the method further includes:
determining a plurality of blood vessel and central reflex diameters using the blood vessel and central reflex edges; and, determining the blood vessel and central reflex parameter values using the plurality of blood vessel and central reflex diameters.

13 ) The method according to claim 12 , wherein the method further includes at least one of:
determining the plurality of blood vessels and central reflex diameters using opposite edge points of edge pixel pairs; and determining the blood vessel and central reflex parameter values by at least one of:
i) selecting a minimum diameter; and;
ii) determining an average diameter.

14 ) (canceled)

15 ) The method according to claim 1 , wherein the method further includes, determining a blood vessel profile using blood vessel reflection parameter values for a plurality of blood vessels in the region.

16 ) The method according to claim 1 , wherein at least one of a blood vessel reflection parameter value and a blood vessel profile are used as a biomarker for predicting at least one of:
i) vascular disease; ii) cerebrovascular disease; iii) APOE ε4 status; and, iv) Alzheimer's disease.

17 ) The method according to claim 1 , wherein the method further includes at least one of:
receiving the fundus image from a fundus camera; receiving the fundus image from a remote computer system via a communications network; and, retrieving the fundus image from a database.

18 ) (canceled)

19 ) A method for quantifying blood vessel reflection associated with the retina comprising:
a) selecting edge start-points of a suitable blood vessel around the optic disc area of a digital image of the eye fundus to constitute the edge start points for grading calculations; b) automatically region cropping to create a cropped digital image around the edge start points and translating the cropped digital image to create a resultant image appropriately orientated for processing; c) processing the resultant image digitally to obtain blood vessel edge and central reflex edge information from the identified vessel edges; and d) measuring the calibres of the outer edges of the blood vessel and the central reflex from the edge information.

20 ) The method as claimed in claim 19 , further including calculating the vessel reflection index being the ratio of the blood vessel calibre and the central reflex calibre to constitute a biomarker for predicting vascular disease of a patient.

21 ) A blood vessel quantification system for quantifying blood vessel reflection associated with the retina comprising:
a) a user interface for enabling an analyst to interact with the system; b) an optic disc (OD) selection process for automatically computing an OD area and a vessel selection (VS) area after the analyst defines the OD centre on the digital image of the fundus using the user interface; c) a mapping, processing and measuring (MPM) process including:
i) an image region selection process for automatically mapping a proximal region around vessel edge start-points and obtaining a selected image for subsequent processing;
ii) an edge detection and profiling process for automatically processing the selected image to obtain and map the vessel edge and central reflex edge profiles;
iii) an edge selection process for automatically selecting vessel edges and central reflex edges closest to the vessel edge start-points to calculate the calibre of the outer vessel edges and the central reflex edges; and
iv) a vessel reflection index measurement process for automatically calculating the vessel refection index of the selected vessel;
wherein the MPM process includes a vessel edge selection process for interactively functioning with the analyst via the user interface to enable the analyst to set the vessel edge start-points from within the VS area after the OD selection process has completed computing the VS area for the MPM process to proceed with performing the aforementioned automated processes.

22 ) The system as claimed in claim 21 , wherein the user interface includes a module to allow an analyst to select an image file containing a digital image of the fundus of the eye of a patient, and enter relevant reference data for subsequent processing by the system.

23 ) (canceled)

Assignees

• Commw Scient Ind Res Org

Inventors

• Kanagasingam Yogesan
• Bhuiyan Alauddin

Classifications

• A61B3/0025 Primary

  characterised by electronic signal processing, e.g. eye models · CPC title

• A61B3/1241

  specially adapted for observation of ocular blood flow, e.g. by fluorescein angiography · CPC title

• A61B3/0041

  characterised by display arrangements · CPC title

• A61B3/0033

  characterised by user input arrangements · CPC title

• A61B3/12 Primary

  for looking at the eye fundus, e.g. ophthalmoscopes (A61B3/13 takes precedence) · CPC title