Automatic OCT Capture

Abstract

An optical coherence tomography (OCT) method including receiving an input from a patient, obtaining a reference image of an object indicating a desired scan position, and obtaining a real-time image of the object, where the reference image is specific to the patient and is obtained remotely. The real-time image is registered to the reference image and the desired scan position is determined. The OCT image is automatically obtained at the desired scan position.

Description

Technical Field

[0001] Cross - Reference to Related Applications This application claims priority to U.S. Provisional Patent Application No. 63 / 365,173, entitled "Automatic OCT Capture," filed on May 23, 2022, the entire contents of which are incorporated herein by reference.

Background Art

[0002] Optical Coherence Tomography (OCT) is a non - invasive imaging technique and is commonly used in ophthalmology. OCT utilizes the principle of interferometry to image and collect information about an object (such as the eye being targeted). Specifically, light from a light source is split into a sample arm that is reflected by the object being imaged and a reference arm that is reflected by a reference object such as a mirror. The reflected light is then combined in a detection arm to generate an interference pattern that is detected by a spectrometer or a photodiode, etc. The detected interference signal is processed to reconstruct the object and generate an OCT image.

[0003] More specifically, structural OCT images and volumes are generated by combining a number of depth profiles (A - scans, e.g., along the Z - depth direction at X - Y positions) into a single cross - sectional image (B - scan, e.g., as an X - Z or Y - Z plane), and by combining a number of B - scans into one volume. These depth profiles are generated by scanning along the X and Y directions. A frontal image of the X - Y plane can be generated by flattening the volume in all or part of the Z - depth direction, and a C - scan image may be generated by extracting a slice of the volume at a given depth.

[0004] One application of OCT imaging is to diagnose various eye conditions and irregularities in ophthalmology. During the examination, it is common for the doctor to determine the positions where additional research and / or imaging are needed. The doctor usually indicates this position to the technician, and the technician performs an OCT scan of the desired position. Therefore, the generated OCT images depend on the skill level of the technician and the understanding of the doctor's requirements. That is, if the OCT images are insufficient, for example, if they are taken at a position different from the desired position, another OCT image may be required.

[0005] Furthermore, generally, patients with eye diseases need to repeat eye scans over a certain period of time. This is usually achieved by regular examinations or scans in the doctor's office. However, repeating the scans requires time and may require securing the time of both the doctor and the technician for execution. SUMMARY OF THE INVENTION MEANS FOR SOLVING THE PROBLEM

[0006] According to an example of the present disclosure, the method comprises receiving an input from a patient, and upon receiving the input: obtaining an existing reference image of an object from a remote database, the existing reference image indicating a desired scan position; obtaining personal information and / or scan settings regarding the patient from the remote database, the personal information and / or scan settings being associated with the existing reference image unique to the patient; obtaining a real-time image of the object; registering the real-time image with the existing reference image; determining a desired scan position on the real-time image based on the registration; and automatically obtaining an OCT image of the object at the desired scan position according to the obtained personal information and / or scan settings.

[0007] In various embodiments of the above example, the existing reference image is initially obtained by a physician; the real-time image is an OCT frontal image; the method further comprises authenticating the patient based on the input from the patient and the obtained personal information; registering the real-time image and determining a desired scan position on the real-time image are performed by a machine learning system; the OCT image at the desired scan position is automatically obtained based on whether the desired scan position is within a threshold range of the center of the real-time image; the method further comprises determining that the desired scan position is not within the threshold range of the center of the real-time image, obtaining a second real-time image of the object, registering the second real-time image as a reference image, and determining a desired scan position on the second real-time image based on the registration of the second real-time image; the scan setting comprises a patient-specific scan pattern, and the OCT image is automatically obtained according to the scan pattern; the method further comprises aligning the OCT imaging system according to the desired scan position; and / or the object is an eye.

[0008] Regarding another example, the system comprises an optical coherence tomography (OCT) imaging system and one or more processors; the one or more processors, collectively, receive an input from a patient and, upon receiving the input: obtain, in response to the input from the patient, an existing reference image of the object from a remote database, the existing reference image indicating a desired scan position; obtain personal information and / or scan settings regarding the patient from the remote database, the personal information and / or scan settings being associated with the existing reference image specific to the patient; obtain a real-time image of the object; register the real-time image as a reference image; determine a desired scan position on the real-time image based on the registration; and automatically obtain an OCT image of the object at the desired scan position using the OCT imaging system according to the obtained personal information and / or scan settings.

[0009] In various embodiments of the above example, the reference image is initially acquired by a physician; the real-time image is an OCT frontal image acquired using an OCT imaging system; one or more processors are further collectively configured to authenticate the use of the system by the patient based on the input from the patient and the personal information obtained; the real-time image is registered to the reference image by one or more processors configured as a machine learning system; the OCT image at the desired scan position is automatically acquired based on whether the desired scan position is within a threshold range centered on the real-time image; one or more processors are further collectively configured to: determine that the desired scan position is not within the threshold range centered on the real-time image, acquire a second real-time image of the object, register the second real-time image to the reference image, and determine the desired scan position on the second real-time image based on the registration of the second real-time image; the scan settings include a patient-specific scan pattern, and the OCT images are automatically acquired according to the scan pattern; one or more processors are further collectively configured to align the OCT imaging system according to the desired scan position; and / or the object is an eye.

Brief Description of the Drawings

[0010]

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DETAILED DESCRIPTION OF THE INVENTION

[0011] In view of the above, the present disclosure relates to automatic image capture, particularly OCT image capture. More specifically, the present disclosure relates to automatic OCT imaging, for example, by using a reference image.

[0012] Using the methods and devices described below, OCT images can be acquired without manual assistance or under the instruction of an examiner. By using automatic OCT imaging, errors due to manually selecting the scan position, such as imaging at the wrong position, can be reduced. Furthermore, automatic OCT scans can facilitate regular OCT imaging (e.g., monitoring the progression of a disease, postoperative analysis, etc.) without the need for an examiner / physician to perform the scan. This realizes time savings for both patients and examiners / physicians. Additionally, according to automatic OCT imaging, a more convenient process for patients can be realized, and patients are freed from the constraints of the clinic's business hours or the availability of examiners / physicians.

[0013] Generally, since automatic OCT imaging relies on reference images that are unique to each patient, it improves efficiency at least in part. This can reduce scan time, improve the acceptable image generation success rate, and reduce the number of scans required. These unique reference images are used as ground truth for known medical conditions, in other words, to represent the known location of a patient's medical condition. In contrast, for example, a "general-purpose" solution may utilize raster scan technology to scan the entire eye since the individual medical conditions regarding the patient are not necessarily known to the automatic imaging system. As a result, such systems and methods have a low success rate, require more scans and scan time, and generally have low efficiency. By using unique reference images, OCT images focused on a particular patient's medical condition can be created, and automatic custom imaging scans of the patient can be provided without a physician.

[0014] Referring to FIG. 1, an OCT imaging system includes a light source 100. The light generated by the light source 100 is split, for example, by a beam splitter (as part of the interferometer optics 108), and sent to a reference arm 104 and a sample arm 106. The light in the sample arm 106 is backscattered from an object such as the retina of the eye 112 or reflected in some other way. The light in the reference arm 104 is backscattered by a mirror 110 or similar object or reflected in some other way. The light from the sample arm 106 and the reference arm 104 is recombined by the optics 108, and the corresponding interference signal is detected by a detector 102. The detector 102 may be a spectrometer, a photodetector, or any other light detection device. The detector 102 outputs an electrical signal corresponding to the interference signal to a processor 114, where it can be stored and processed in OCT signal data.

[0015] Processor 114 may then further generate a corresponding structural image or angiographic image or volume, or alternatively perform an analysis of the data. Processor 114 may also be associated with an input / output interface (not shown) including a display for outputting the processed images or information related to the analysis of those images. The input / output interface may include hardware such as buttons, keys, or other controls for receiving user input into the system. In some embodiments, Processor 114 may also be used to control the light source and imaging process.

[0016] FIG. 2A shows an automated imaging terminal 200 of the present disclosure. The imaging terminal 200 shown in the figure comprises a computer 202 including at least one processor 204, local storage 206a, and an input / output (I / O) device 208. The I / O device 208 may be any input / output device that enables communication and selection by a user or patient, such as a keyboard, mouse, selection buttons, LED display, touch screen, etc. In some embodiments, the I / O device 208 comprises a wireless communication device that communicates using a wireless communication standard such as Bluetooth or Wi-Fi and can communicate with a portable device such as a mobile phone. The I / O device 208 can also communicate with a remote database 206b via a wireless communication standard, Ethernet, or an Internet connection. The remote database 206b may be a cloud database, an on-premises database, or the like.

[0017] The automated imaging terminal 200 further comprises a dedicated real-time imaging system 210 (fundus camera, IR camera, SLO camera, or the like) and an OCT imaging system 212. The OCT imaging system 212 may be the one discussed above and shown in FIG. 1. The real-time imaging system 210 and the OCT imaging system 212 can share a viewport 211, which can be accessed by a patient for using the automated imaging terminal 200. The viewport 211 may comprise at least an optical system configured to image the patient's eye by both the real-time imaging system 210 and the OCT imaging system 212.

[0018] In some embodiments as shown in FIG. 2B, the automated imaging terminal 200 does not include a dedicated real-time imaging system 210. Instead, the OCT imaging system 212 also functions as a real-time imaging system by acquiring real-time high-speed anterior OCT images, or the like.

[0019] The computer 202 communicates with the real-time imaging system 210 and the OCT imaging system 212 and can receive information from the real-time imaging system 210 and the OCT imaging system 212. For example, images acquired by the real-time imaging system 210 and the OCT imaging system 212 may be analyzed by at least one processor 204 (the processing may be distributed among one or more processors in any manner), stored in the local storage 206a, and / or stored in the remote database 206b. The at least one processor 204 can also adjust various camera functions and alignments of the imaging systems 210, 212 having the viewport 211 by using computer-generated commands or by controlling physical actuators and motors.

[0020] The automated imaging terminal 200 may be in the design of a kiosk or the like and can be placed in a public place for easy access. A patient can walk up to the public automated imaging terminal 200 and receive regular eye scans at a convenient time without the need to schedule an appointment with, for example, a technician or a doctor. The automated imaging terminal 200 can automatically acquire an OCT image from a desired scan position indicated by a reference image specific to the patient without operator input.

[0021] The reference image may be various types of images and can be acquired in various ways. For example, as shown in FIG. 5A, a doctor can manually mark a desired scan position within the chart drawing 510. The chart drawing 510 is a basic drawing or a simplified depiction of the human eye and is marked (e.g., with an "X") to indicate the desired scan position relative to anatomical landmarks. Additionally, or alternatively, the reference image can be acquired using a fundus camera that generates a fundus image 512 as shown in FIG. 5B. This fundus image can also be marked (e.g., with an "X") to indicate the target scan position. The reference image may be an OCT image (e.g., a frontal image, a structural C-scan, an angiography image, or the like) 514 as shown in FIG. 5C. The frontal OCT image 514 may be acquired using an OCT imaging system as shown in FIG. 1. As described above, the OCT image 514 can be marked (e.g., with an "X") to indicate the desired scan position.

[0022] The reference image can represent prior knowledge regarding the patient's medical condition as described above. However, in some embodiments, the reference image can be collected and analyzed by the automated imaging terminal 200 itself or a similar system.

[0023] In any case, the scan positions are marked on the reference image and guide subsequent OCT imaging. In the example of a prior reference image, the scan positions may be manually marked by a physician or automatically identified by analysis of the reference image. The physician can manually mark the reference image on a copy of the fundus photograph using computer software or a writing instrument. The desired scan positions may be indicated using colored pixels or other marks and may be stored as coordinates on the X-Y axis (e.g., as digital coordinates) or as specific pixel position information or the like. The reference image is patient-specific and thus may be unique to each patient. For example, the reference image may indicate specific desired scan positions for observing a particular patient's retinopathy. In some embodiments, the reference image may indicate general positions, for example, desired scan positions near the optic nerve for observing the progression of glaucoma.

[0024] The scan positions may be automatically determined and marked, for example, based on analysis of the reference image. In some embodiments, in the automatic imaging terminal 200, image processing techniques such as computer vision and / or machine learning can be used to determine the region of interest of a real-time fundus image obtained by the real-time imaging system 210 or a real-time anterior OCT image obtained using the OCT imaging system 212. The computer 202 and / or the processor 204 can use image processing techniques as described above, including computer vision and machine learning. The region of interest or the desired scan position may be a specific medical condition of the patient.

[0025] The reference image may be input, for example, into a machine learning system trained to identify regions of interest based on anomalies within the image. Such techniques may be those described in U.S. Patent No. 11,132,797, titled "AUTOMATICALLY IDENTIFYING REGIONS OF INTEREST OF AN OBJECT FROM HORIZONTAL IMAGES USING A MACHINE LEARNING GUIDED IMAGING SYSTEM," the entirety of which is incorporated herein by reference, and / or those described in U.S. Patent Application 16 / 552,467, titled "MULTIVARIATE AND MULTI-RESOLUTION RETINAL IMAGE ANOMALY DETECTION SYSTEM," the entirety of which is incorporated herein by reference.

[0026] The acquisition and marking of the reference image may be performed during a patient's examination and may be stored, for example, within a physical or virtual file of the patient for subsequent use. The virtual file may be stored in a remote database 206b such as a computer's local memory, an on-premises database, or cloud-based storage. For example, a patient may be able to have their physician store the reference image on file. The physician may be able to indicate a desired scan location on the reference image using the techniques described above. The reference image with the desired scan location may be stored in the cloud or otherwise in the remote database 206b for access by the automatic imaging terminal 200.

[0027] Referring to FIG. 3, a patient can initiate an automatic capture 301 by using a button on the device, such as a start button, or by accessing the automatic imaging terminal 200 using a personalized login. In some embodiments, the patient can use their personal mobile phone to scan a machine-readable optical image, such as a QR code, located on or near the automatic imaging terminal 200. The QR code can direct the user to a web application or mobile app, or generate a text message, where the patient can sign into their personal account and indicate which automatic imaging terminal 200 they are located at. For example, the patient can indicate their location using a Global Positioning System (GPS), a prompt from the app, the GPS location of the automatic imaging terminal 200, or a unique QR code associated with a particular automatic imaging terminal 200.

[0028] The automatic imaging terminal 200 can then communicate with a remote database 206b via the Internet or other network to obtain the patient's reference image, personal information, scan settings, or the like 302. For example, the scan settings can be patient-specific and can include resolution, brightness, saturation, contrast, size, scan pattern, or similar image settings that can be used when the real-time imaging system 210 or the OCT imaging system 212 acquires an image / scan. Personal information can include name, gender, age, height, weight, medical history, and / or pathology information and the like. Further, for example, additional instructions can include the starting center position of the real-time imaging system 210 or the OCT imaging system 212, the display of the number of OCT images or scans to be acquired, the type of registration method, or other information regarding the acquisition of real-time or OCT images.

[0029] In some embodiments, the use of the automated imaging terminal 200 may first require patient authentication. The authentication can be determined in various ways. For example, the automated imaging terminal may authenticate a patient if the patient has a reference image on file with the owner / operator of the automated imaging terminal 200. In particular, after the patient starts the automatic capture 301, the automated imaging terminal 200 then communicates with the remote database 206b and may include patient information such as patient ID, login, name, address, or the like. The remote database 206b can use this patient information to determine whether the patient belongs to the owner / operator of the automated imaging terminal 200. For example, if the automated imaging terminal 200 is owned / operated by a physician or a service provider for a physician, the automated imaging terminal 200 determines whether the patient has personal information or a reference image on a file used by that physician or service provider.

[0030] This authentication can be facilitated through the local storage 206a and / or the remote database 206b, which can store patient information and / or reference images for the physician or service provider. Thus, the patient information entered by the patient into the automated imaging terminal 200 is simply compared with the records stored in the local storage 206a and / or the remote database 206b, and a match can be identified. When a match is determined, the patient is alerted that they have been authenticated, the use of the automated imaging terminal 200 is unlocked, and the patient can continue to use the automated imaging terminal 200 to automatically capture OCT images.

[0031] If the corresponding patient information is not determined, the patient may be warned and, for example, asked to contact their physician (e.g., to schedule an appointment). In some embodiments, the physician may be proposed or automatically contacted by the automated imaging terminal 200. In some embodiments, the automated imaging terminal 200 may be used to collect a reference image for that patient and then analyzed in real time (by local or remote services) to facilitate further imaging or transmitted to the physician for further analysis. The automated imaging terminal 200 may also recommend or automatically propose such a physician and / or request physician information from the patient.

[0032] Even if patient information and / or reference images are stored, additional information may be required to authenticate the patient. For example, the physician may perform a periodic review of their patient files and be able to indicate the admissibility of the reference images in the stored patient information. For example, if it is determined that the reference image on file is old, expired, of poor quality, associated with another physician, etc., the physician can indicate this along with the patient information. If such information exists, it may prevent the patient from authenticating the use of the automated imaging terminal 200, and the automated imaging terminal 200 may also warn the patient of such problems, automatically contact the physician, or propose a physician for the patient to contact.

[0033] In some embodiments, the owner / operator of the automated imaging terminal 200 provides access to the automated imaging terminal 200 as a service. For example, the owner / operator can provide this service to multiple physicians, where the automated imaging terminal 200 can provide the service to any patient of those physicians. The automated imaging terminal 200 can obtain additional information 302 indicating whether a physician is still subscribed to the owner / operator's service, and based on this information, can authenticate patient use. In some embodiments, each patient subscribes to the service, thereby granting the patient access to the automated imaging terminal 200. Thus, authentication may be performed based on the patient's subscription.

[0034] The automated imaging terminal 200 can use the acquired reference images and other information 302 to obtain an automated real-time image having a desired scan position 303. For example, using the exemplary method described in FIG. 4, the automated imaging terminal 200 can obtain reference images 401 via the remote database 206b and store them in the local storage 206a. The automated imaging terminal 200 can then use the real-time imaging system 210 to obtain a real-time image 402. Referring to FIGS. 4 and 6, the method can obtain a real-time image 402 from the real-time imaging system 210 of the automated imaging terminal 200. For example, a real-time image can be obtained from a fundus camera, an infrared video camera, a scanning laser ophthalmic image, a front OCT image, etc.

[0035] To perform imaging appropriately, the automated imaging terminal 200 can use the real-time imaging system 210 and the processor 204 to determine whether the patient's eye is aligned within the viewport 211. In some embodiments, using machine learning techniques and the real-time imaging system 210, the processor 204 can detect the macula of each of the patient's eyes and determine whether the patient is centered within the viewport 211. If the patient is not centered within the viewport 211, the processor 204 can use the I / O device 208 to notify the patient to adjust through voice notifications, voice commands, or visual displays. LEDs or similar displays can be used to provide a visual indication of how to center the patient's eye. For example, a circle displayed on an LED display can indicate the desired position of the patient's eye, and a second set of circles representing the real-time position of the patient's eye can be provided to give the patient real-time feedback on how to adjust to the desired positioning. In other embodiments, "aiming points" can be displayed to guide the patient to align themselves within the viewport 211. Other alignment techniques, such as the display of a real-time video feed, lights indicating the center or focus of the imaging device, rings of lights, audible feedback, etc. can be used. The processor 204 can use software implementing image processing techniques and / or machine learning techniques to determine when the patient is properly aligned.

[0036] The acquired real-time image 402 is then adjusted to register (403) the real-time image 603 and the reference image 601. In image registration 403, different data sets can be transformed into one coordinate system, enabling the alignment of images of the same patient at similar positions, different times, and different viewpoints. Image registration can be achieved in various ways, such as feature-based, intensity-based, etc. In some embodiments, an exemplary method uses feature-based registration techniques to identify the same anatomical structure 602 found in two spatially corresponding images (similar positions). Once the same structure is identified, the two images can be associated by the relative positions of the anatomical structure 602.

[0037] As shown in FIG. 6, an exemplary feature-based registration technique uses a reference image 601 having a desired scan position 604 and anatomical features 602, and a real-time image 603 including a scan center 608 and anatomical features 602. This exemplary method can associate the anatomical features 602 of the real-time image 603 with the anatomical features 602 of the reference image 601 using a feature-based registration technique 610. The anatomical features 602 can be various parts of the eye, such as the macula, optic nerve, blood vessels, etc.

[0038] The feature-based method can establish relationships between multiple features or distinct points within an image to realize a geometric transformation for mapping the real-time image 603 to the reference image 601. For example, the feature-based registration technique 610 may include various image transformations, such as rotation, scaling, translation, and other affine transformations, to align at least one orientation of the image, and can map or fit the real-time image 603 to the same coordinate system as the reference image 601. Other transformation methods, such as non-rigid transformation, multi-parameter transformation, etc., can also be used. The transformation can be realized using image processing and / or registration techniques, and / or machine learning techniques. Such techniques may include, for example, feature-based alignment, model-fitting alignment, pixel-based alignment.

[0039] By registering the real-time image 603 together with the reference image 601, a registered image 605 in which the real-time image 603 is mapped to the reference image 601 can be generated, and the desired scan position 604 of the reference image 601 and the scan center 608 of the real-time image can be held within the registered image 605. That is, the registered image 605 contains the desired scan position 604 of the reference image 601 in relation to the scan center 608 of the real-time image 603. In some embodiments, the transformation can be performed directly on the real-time image, and thus no additional registered images are generated.

[0040] The exemplary method can then use the transformation 612 to transform the registered image 404 and obtain the desired scan position 604 within the real-time image 603. In some embodiments, the inverse transformation of the transformation used in the registration process 610 is used to obtain the desired scan position 604 within the real-time image 603. For example, if the real-time image is rotated 45° clockwise during the registration process 610 to register the real-time image 603 onto the reference image 601, during the transformation of the registered image 605, the transformation 612 can include rotating 45° counterclockwise, i.e., the inverse transformation of the transformation during the image registration process. The transformation process 404 includes only pixel information from the real-time image 603 while holding the desired scan position 604 from the reference image 601. In other words, the registration transformation process transforms the desired scan position to the real-time image 603.

[0041] When associating the desired scan position with the real-time image, the coordinates or position information of this desired scan position (e.g., the center of the viewport 211 and for the resulting image) can then be obtained and / or stored for future use, for example, in the local storage 206a or the remote database 206b.

[0042] Returning to FIG. 3, the automatic imaging terminal 200 can determine the receptivity of the real-time image based on a number of factors such as proximity to the desired scan position, scan instructions, noise level, etc. For example, depending on the distance between the scan center 608 and the desired saved position 604, the viewport 211 and / or the real-time imaging system 210 can be adjusted to bring the scan center 608 closer to the desired scan position 604. The real-time imaging system 210 can then acquire another real-time image of the new position and repeat the exemplary method as described in FIG. 4 until the scan center 608 of the real-time image falls within an acceptable vicinity of the desired position 604. Referring to FIG. 7 for example, the real-time image 700 with the desired position indicator 702 and the scan center 706 saved can be determined to be acceptable because the desired position indicator 702 is within a predetermined proximity threshold 704 (e.g., number of pixels or determined distance).

[0043] The automatic imaging terminal 200 can further indicate to the patient whether the real-time image obtained from the real-time imaging system 210 is acceptable, for example, by using the I / O device 208 for generating light, notifications, or voice commands generated on the automatic imaging terminal 200, or by using similar actions. For example, if the patient is blinking (or otherwise has unstable eyes) and the real-time imaging system 210 is preventing an acceptable image from being taken, the I / O device 208 can use a voice command to instruct the patient to keep their eyes open. The processor 204 can use image processing techniques and / or machine learning techniques for detecting eye movement, instability, and / or blinking. For example, the processor can use image detection software that detects blinking indicated by a real-time image with large dark bands or dark regions in the fundus image or frontal image.

[0044] For example, referring to FIG. 9, the real-time front image 904-2 has a plurality of black bands indicating the patient's blinks, while the real-time front image 904-1 has no black bands and is registered in the reference fundus image 902. The processor 204 can also implement a blink / instability / motion threshold test to determine the appropriate time to acquire a real-time image or an OCT image. For example, the processor 204 can detect that the patient is not blinking / is stable and / or is in the correct position for a given time before acquiring a real-time image or an OCT image. For example, when the patient has not blinked for several seconds and is correctly positioned in the viewport 211.

[0045] In some embodiments, an LED display or the like visible from the viewport 211 can generate a focus for the patient to focus on during the imaging process. The LED display can be overlaid on the optical system of the viewport 211 to enable the patient to stay in the viewport 211 during the imaging process. The LED display can also generate light that blinks or lights up to indicate various states of the process. For example, green light indicating that the image is acceptable, or yellow light indicating that the image is not yet acceptable.

[0046] When the automatic scan meets the acceptance (quality) criteria, the OCT imaging system 212 automatically acquires the OCT image 305 at the determined desired scan position. For example, if it is determined that the real-time image 700 is acceptable, the automatic imaging terminal 200 can then acquire the OCT image by adjusting (e.g., centering) the viewport 211 and / or the OCT imaging system 212 on the same scan center 706 as the real-time image 700. For example, as shown in FIG. 8, the OCT imaging system 212 can automatically acquire 16 structured OCT B scans numbered from #0 to #15 centered on the scan center 706 of the real-time image 700 or the desired scan position 702. The automatic imaging terminal 200 can appropriately adjust the OCT imaging system using an actuator, a motor, etc. In another embodiment, the automatic imaging terminal 200 keeps the OCT imaging system 212 and the real-time imaging system 210 centered at the same position throughout the process. Thus, when the automatic real-time scan meets the desired threshold, the automatic imaging terminal 200 is within the position for acquiring the OCT image.

[0047] The automatic imaging terminal 200 can acquire the OCT image 305 using various scan patterns and techniques, such as radial scan, circle scan, vertical scan, horizontal scan, etc. These scan patterns may be indicated by scan settings obtained using a reference image and may be specific to each patient or specialized. Thus, if a particular scan method / pattern is desired by a physician or is more suitable for that particular patient or medical condition, that scan method / pattern can be automatically indicated and utilized by the automatic imaging terminal 200.

[0048] Computer 202 can store the acquired OCT images in local storage 206a or remote database 206b. In some embodiments, computer 202 can store the acquired OCT images in local storage 206a for later uploading to remote database 206b. For example, if the internet connection is disconnected or interrupted during the scan, the automated imaging terminal 200 can end the scan process, save the acquired OCT images locally, and upload the OCT images to the remote database after the internet connection is restored. Computer 202 can link the acquired OCT images to a patient using previously acquired patient information. In some embodiments, the OCT images are stored in a patient's file on remote database 206b and later reviewed by a physician. The physician can then modify the desired scan location within the reference image or the instructions of the automated imaging terminal 200 if the physician desires.

[0049] This enables continuous review and feedback from the physician without scheduling an appointment. The physician may also include instructions to be presented to the patient during the next visit to the automated imaging terminal 200. For example, if the physician finds an abnormality, the physician can present a reminder or notification to the user to contact the physician for further evaluation. The reminder or notification can be displayed on the device via viewport 211 or on an information LED display located on the automated imaging terminal 200. In some embodiments, the reminder or notification can be sent directly to the patient using other forms of communication, such as the patient's mobile device.

[0050] Using the exemplary method described above, the automated imaging terminal 200 obtains OCT images 305 specific to each patient because the method can rely on information specific to that patient. For example, a reference image of the patient can be marked by a physician who performs the patient's examination and can know details about the patient's medical condition. This information may be stored and / or associated with the patient-specific reference image, and as a result, can be obtained and used by the automated imaging terminal 200.

[0051] It should be understood that the various features described above can be used alone or in any combination thereof. Furthermore, those skilled in the art of the relevant field to which the claimed examples pertain should understand that variations and modifications can be envisioned.

Claims

1. Receiving an input from a patient, and upon receiving the input, acquiring, from a remote database, an existing reference image of an object, the existing reference image indicating a desired scan position; acquiring, from the remote database, personal information and / or scan settings related to the patient, the personal information and / or scan settings associated with the existing reference image specific to the patient; acquiring a real-time image of the object; registering the real-time image with the existing reference image; determining, based on the registration, the desired scan position on the real-time image; automatically acquiring an OCT image of the object at the desired scan position according to the acquired personal information and / or scan settings; A method comprising the above.

2. The method according to claim 1, wherein the existing reference image was initially acquired by a doctor.

3. The method according to claim 1, wherein the real-time image is an OCT frontal image.

4. Further comprising authenticating the patient based on the input from the patient and the acquired personal information. The method according to claim 1.

5. The method according to claim 1, wherein registering the real-time image and determining the desired scan position on the real-time image are performed by a machine learning system.

6. The method according to claim 1, wherein the OCT image at the desired scan position is automatically acquired based on whether the desired scan position is within a threshold range of the center of the real-time image.

7. Determining that the desired scan position is not within the threshold range of the center of the real-time image; acquiring a second real-time image of the object; registering the second real-time image with the reference image; determining, based on the registration of the second real-time image, the desired scan position on the second real-time image; The method according to claim 6, comprising the above.

8. The method according to claim 1, wherein the scan settings comprise a scan pattern specific to the patient, and the OCT image is automatically acquired according to the scan pattern.

9. Further comprising aligning an OCT imaging system according to the desired scan position. The method according to claim 1.

10. The method according to claim 1, wherein the object is an eye.

11. A system comprising an optical coherence tomography (OCT) imaging system and one or more processors, the system being such that the one or more processors, collectively, receive an input from a patient, and upon receiving the input, in response to the input from the patient, obtain an existing reference image of an object from a remote database, the existing reference image indicating a desired scan position, obtain personal information and / or scan settings regarding the patient from the remote database, the personal information and / or scan settings being associated with the existing reference image specific to the patient, obtain a real-time image of the object, register the real-time image as a reference image, determine the desired scan position on the real-time image based on the registration, automatically obtain an OCT image of the object at the desired scan position using the OCT imaging system according to the obtained personal information and / or scan settings.

12. The system according to claim 11, wherein the reference image was initially obtained by a physician.

13. The system according to claim 11, wherein the real-time image is an OCT frontal image obtained using the OCT imaging system.

14. The one or more processors are further collectively configured to authenticate the use of the system by the patient based on the input from the patient and the obtained personal information.

15. The system according to claim 11, wherein the real-time image is registered as the reference image by one or more processors configured as a machine learning system.

16. The system according to claim 11, wherein the OCT image at the desired scan position is automatically obtained based on whether the desired scan position is within a threshold range of the center of the real-time image.

17. The one or more processors are further collectively configured to determine that the desired scan position is not within the threshold range of the center of the real-time image, obtain a second real-time image of the object, register the second real-time image as the reference image, The system according to claim 16, wherein the desired scan position on the second real-time image is determined based on the registration of the second real-time image. **Claim 18** The system according to claim 11, wherein the scan setting comprises a patient-specific scan pattern, and the OCT image is automatically acquired according to the scan pattern. **Claim 19** The one or more processors are further collectively The system according to claim 11, wherein the OCT imaging system is configured to be aligned according to the desired scan position. **Claim 20** The system according to claim 11, wherein the object is an eye.

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