Mapping and diagnosis of macular edema by optical coherence tomography
The present invention discloses a method for comparing the detection of clinically significant diabetic macular edema by an optical coherence tomography (OCT) grid scanning protocol and biomicroscopic examination. Also provided are computer implemented, automated systems for performing the method thereof and computer readable media encoding the method thereof.
1. A computer implemented system for identifying regions of macular edema in a subject, comprising:
an input unit adapted for receiving an input retinal thickness map generated by an optical coherence tomography device; and
a processing unit configured to perform a method for analyzing the retinal thickness map, comprising the steps of:
comparing the input retinal thickness map with a normal reference map to identify regions of abnormal retinal thickness in the macular region,
wherein the normal reference map is compiled from retinal thickness maps of a population with normal eyes, and wherein a point on the input retinal thickness map is abnormal if it meets predetermined comparison criteria,
whereby a region of macular edema is identified based on comparisons of the retinal thickness maps.
2. The system of claim 1 , wherein the normal reference map is stored on an internal storage of the system.
3. The system of claim 1 , wherein the normal reference map is stored on a remote central database.
4. The computer implemented system of claim 1 , wherein said input retinal thickness map is generated by an optical coherence tomography device employing a scanning pattern comprising a plurality of evenly spaced axial scans forming a circular grid.
5. The computer implemented system of claim 1 , wherein said normal reference map is compiled from retinal thickness maps of a population with normal eyes, and said normal reference map comprises a mean value map and a standard deviation map.
6. The computer implemented system of claim 5 , wherein said predetermined criteria are based on the mean value map and standard deviation map of the normal reference map.
7. The computer implemented system of claim 1 , wherein said processing unit is configured to perform a further step of identifying an edema kernel by finding one or more locations on the input retinal thickness map where the value is greater than a predetermined standard deviation above the mean value at the same location of the normal reference map.
8. The computer implemented system of claim 7 , wherein said edema kernel are locations having values greater than 2.33 standard deviation above a normal reference mean at the corresponding location of the reference map.
9. The computer implemented system of claim 7 , wherein said processing unit is configured to perform the further step of identifying zones of edema by expanding a region of edema via assessing the thickness of locations neighboring an edema kernel and adding the locations to the region if it has a thickness greater than a predetermined thickness.