AUTOMATED OCT ACQUISITION

Abstract

Method comprising: Receiving an input from a patient, and after receiving the input: Acquiring an existing reference image of an object from a remote database, wherein the existing reference image indicates a desired scanning position; Capturing personal information and / or scan settings relating to the patient from the remote database, whereby the existing reference image is unique to the patient and is linked to personal information and / or scan settings; Capturing a real-time image of the object; Registering the real-time image with the existing reference image; Determining the desired scan position on the real-time image based on the registration; and Automatically capture an OCT image of the object at the desired scan position and according to the captured personal information and / or scan settings.

Claims

[1] Method comprising: Receiving input from a patient, and after receiving the input: Acquiring an existing reference image of an object from a remote database, wherein the existing reference image indicates a desired scanning position; Capturing personal information and / or scan settings relating to the patient from the remote database, whereby the existing reference image is unique to the patient and is linked to personal information and / or scan settings; Capturing a real-time image of the object; Registering the real-time image with the existing reference image; Determining the desired scan position on the real-time image based on the registration; and Automatically acquire an OCT image of the object at the desired scan position and according to the captured personal information and / or scan settings. [2] The method of claim 1, wherein the pre-existing reference image was originally obtained by a clinician. [3] The method of claim 1, wherein the real-time image is an OCT facial image. [4] The method of claim 1, further comprising: Authorize the patient based on the personal information entered and collected by the patient. [5] The method of claim 1, wherein registering the real-time image and determining the desired scan position on the real-time image is performed by a machine learning system. [6] The method of claim 1, wherein the OCT image at the desired scanning position is automatically acquired based on whether the desired scanning position is within a threshold range around the center of the real-time image. [7] The method of claim 6, further comprising: Determine that the desired scan position is not within the threshold range around the center of the real-time image; Capturing a second real-time image of the object; Registering the second real-time image with the reference image; and Determining the desired scan position on the second real-time image based on the registration of the second real-time image. [8] The method of claim 1, wherein the scan settings include a patient-specific scan pattern and the OCT image is automatically acquired according to the scan pattern. [9] The method of claim 1, further comprising: Align the OCT imaging system according to the desired scan position. [10] The method of claim 1, wherein the object is an eye. [11] System comprising: an optical coherence tomography (OCT) imaging system; one or more processors that are collectively configured to: Receiving input from a patient, and after receiving the input: Acquiring a pre-existing reference image of an object from a remote database in response to a patient input, the pre-existing reference image indicating a desired scan position; Capturing personal information and / or scan settings relating to the patient from the remote database, whereby the existing reference image is unique to the patient and is linked to personal information and / or scan settings; Capturing a real-time image of the object; Registering the real-time image with the reference image; Determining the desired scan position on the real-time image based on the registration; and Automatically acquire an OCT image of the object at the desired scanning position using the OCT imaging system according to the acquired personal information and / or scan settings. [12] The system of claim 11, wherein the reference image was originally acquired by a clinician. [13] The system of claim 11, wherein the real-time image is an OCT facial image acquired with the OCT imaging system. [14] The system of claim 11, wherein the one or more processors are further configured to: Authorize the patient's use of the system based on the patient's input and the personal information collected. [15] The system of claim 11, wherein the real-time image is registered with the reference image by one or more processors configured as a machine learning system. [16] The system of claim 11, wherein the OCT image at the desired scan position is automatically acquired based on whether the desired scan position is within a threshold range about a center of the real-time image. [17] The system of claim 16, wherein the one or more processors are further configured to: Determine that the desired scan position is not within the threshold range around the center of the real-time image; Capturing a second real-time image of the object; Registering the second real-time image with the reference image; and Determining the desired scan position on the second real-time image based on the registration of the second real-time image. [18] The system of claim 11, wherein the scan settings include a patient-specific scan pattern and the OCT image is automatically acquired according to the scan pattern. [19] The system of claim 11, wherein the one or more processors are further configured to: Align the OCT imaging system according to the desired scan position. [20] The method of claim 11, wherein the object is an eye.