Eye tracking method, device, and storage medium used in anterior segment OCTA

Abstract

The present disclosure provides an eye tracking method, device, apparatus, and storage medium for use in anterior segment OCTA. The eye tracking method for use in anterior segment OCTA includes acquiring two consecutive frames of pupil diagrams, extracting contours for each of the two frames of pupil diagrams to obtain two corresponding pupil contours, determining whether the two pupil contours are similar to a reference contour, and, in response to the two pupil contours being similar to the reference contour, calculating a center position shift of one of the two pupil contours relative to the other pupil contour.

Description

[Technical field]

[0001] This application claims priority to a Chinese patent application bearing application number 202111489187.2, filed with the China Patent Office on December 7, 2021, the entire contents of which are incorporated herein by reference.

[0002] The present disclosure relates to the technical field of eye tracking, and to an eye tracking method, device, apparatus, and storage medium used, for example, in anterior segment Optical Coherence Tomography Angiography (OCTA). [Background technology]

[0003] OCTA is a new non-invasive fundus imaging technique that is first applied to the posterior segment, i.e., the fundus. It can recognize the kinetic information of retinal-choroidal blood flow with high resolution and capture the circulation of retinal-choroidal microvessels in biological tissue. OCTA has unique advantages in detecting the changes in normal retinal-choroidal blood vessels, as well as disease management, follow-up, and treatment effect detection. In the anterior segment, the blood flow signal of the scanned area is obtained through the signal changes of optical coherence tomography (OCT), which scans the same cross section multiple times, and OCTA images of the scanned area of ​​the anterior segment can be obtained by scanning multiple cross sections continuously.

[0004] Current OCTA is not suitable for all patients, and OCTA images can be inaccurate if the patient has poor fixation, frequent blinking, or eye movement. Summary of the Invention

[0005] The present disclosure provides an eye tracking method, device, apparatus, and storage medium for use with anterior segment OCTA that can improve the problem that OCTA is not suitable for all patients and that OCTA images can be inaccurate, especially when the patient has poor fixation, frequent blinking, or eye movement.

[0006] In a first aspect of the present disclosure, obtaining two consecutive frames of pupillograms; extracting a contour from each of the two frames of pupil diagrams to obtain two corresponding pupil contours; determining whether the two pupil contours are similar to a reference contour; and calculating a deviation in a center position of one of the two pupil contours relative to the other pupil contour in response to the two pupil contours being similar to the reference contour.

[0007] In a second aspect of the present disclosure, an acquisition module configured to acquire two consecutive frames of pupillograms; an extraction module configured to extract a contour of each of the two frames of pupil diagrams to obtain two corresponding pupil contours; a determining module configured to determine whether the two pupil contours are similar to a reference contour; and a calculation module configured to calculate a central position shift of one of the two pupil contours relative to the other pupil contour in response to the two pupil contours being similar to a reference contour.

[0008] In a third aspect of the present disclosure, there is provided an electronic device, comprising a memory and a processor, the memory storing a computer program, the electronic device implementing, when executed by the processor, an eye tracking method for use in an anterior segment OCTA according to the embodiments of the present disclosure.

[0009] In a fourth aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements an eye tracking method for use in an anterior segment OCTA as described in the embodiments of the present disclosure. [Brief description of the drawings]

[0010] [Figure 1] FIG. 2 is a normally photographed pupil diagram according to an embodiment of the present disclosure. [Diagram 2] FIG. 1 is a flow diagram of an eye tracking method for use in anterior segment OCTA according to an embodiment of the present disclosure. [Diagram 3] 4 is a schematic diagram of a pupil contour extraction process according to an embodiment of the present disclosure; FIG. [Figure 4] FIG. 13 is a schematic diagram showing dissimilarities between a pupil contour and a reference contour according to an embodiment of the present disclosure. [Diagram 5] FIG. 2 is a schematic diagram showing similarities between a pupil contour and a reference contour according to an embodiment of the present disclosure. [Figure 6] FIG. 2 is a structural schematic diagram of an eye tracking device used in an anterior segment OCTA according to an embodiment of the present disclosure. [Figure 7] FIG. 1 is a structural schematic diagram of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, technical solutions in the embodiments of the present disclosure will be described with reference to the drawings in the embodiments of the present disclosure.

[0012] The eye tracking method used in the anterior segment OCTA according to the embodiments of the present disclosure is applicable to the field of eye tracking technology.

[0013] OCTA detects the movement of red blood cells in the vascular lumen by measuring the change in OCT signals obtained by scanning the same cross section multiple times, and obtains a complete 3D retina-choroidal vascular image after integrating the information from successive en face OCT images. Among them, en face OCT is a transverse tomographic imaging technique that uses software calculations to process conventional high-density B-scan images.

[0014] OCTA is not suitable for all patients. Only when the patient's fixation is good and the optic media is transparent, can the OCTA image with good blood flow continuity and high scanning signal quality be obtained. The time required for a single OCTA blood flow scan is determined by the scanning range and light source frequency. When the scanning range is large and the requirements for the light source frequency are high, the OCTA shooting time is also long, which results in the patient having poor fixation, frequent blinking, and eye movement, which leads to poor OCTA scanning signal strength and poor image quality.

[0015] Therefore, the introduction of eye tracking is very necessary in the scanning process, which can realize automatic measurement of the patient's pupil position, recognize and eliminate the blinking and eye movement situations, and obtain the movement direction and magnitude between the two consecutive positions of high quality pupil maps, so that the subsequent OCTA photography can be more accurate.

[0016] Fig. 1 is a normally photographed pupil diagram according to an embodiment of the present disclosure. Referring to Fig. 1, in the related art, a typical strategy for recognizing a pupil includes steps such as image filtering, image binarization, edge detection and ellipse fitting. Meanwhile, when blinking occurs, that is, when a part or the whole of the pupil is blocked by eyelids or eyelashes, the blocked part is generally excluded and only the effective area is used to perform ellipse fitting.

[0017] The process of the ellipse fitting method is as follows: first, extract the region of interest from the image by a mask, then obtain a threshold value from the histogram to binarize the image, then use an edge following algorithm to extract the contour from the binarized image, and finally perform ellipse fitting on the extracted contour. If the error between the fitted ellipse and the original contour is greater than a threshold value, a random consensus algorithm is used to discard the outliers.

[0018] In the related art, many technical solutions require binarizing the image, but it is not easy to determine the threshold required for binarization. Once the image quality is poor or the threshold is not selected properly, the area marked by the binarized image is not necessarily the pupil.

[0019] In addition, in many technical solutions, the recognition of the pupil position is obtained by fitting an ellipse. However, doing so has some drawbacks. For example, in an ophthalmic examination, the patient's pupil may already be deformed, and in this case, fitting with a pre-set shape (such as an ellipse) will lead to large errors. Moreover, fitting with an ellipse itself will also lead to errors.

[0020] There are no eye tracking solutions specifically targeted at anterior segment OCTA yet, and customizing the solution for this would additionally require knowing whether the patient is blinking or not, something that most technology solutions have never mentioned.

[0021] To address the above technical problems, embodiments of the present disclosure provide an eye tracking method for use in anterior segment OCTA, which in some embodiments can be implemented by electronic devices.

[0022] 2 is a flow diagram of an eye tracking method used in an anterior segment OCTA according to an embodiment of the present disclosure. Referring to FIG. 2, the eye tracking method used in the anterior segment OCTA in this embodiment includes the following:

[0023] In operation 201, two consecutive frames of pupillograms are acquired.

[0024] In the embodiment of the present disclosure, the two consecutive frames of pupillary images are arbitrarily selected from the normally captured pupillary images when performing OCTA image recognition on a patient, and the two consecutive frames of pupillary images can be obtained by an optical diagnostic imaging device.

[0025] In the embodiment of the present disclosure, the number of image frames to be captured is determined according to the resolution of the optical diagnostic imaging device, and generally, the number of image frames to be captured within one second is 30 frames, 60 frames, or 120 frames. Within a certain time, the optical diagnostic imaging device can capture multiple frames of images.

[0026] In an embodiment of the present disclosure, the device for performing diagnostic imaging based on optical principles includes an OCT imaging device and a pupil camera imaging device.

[0027] In order to facilitate the explanation of the eye tracking method used in the anterior segment OCTA, an arbitrary group of two consecutive frames of pupillary images from each group of multiple frame images will be selected as the two consecutive frames of pupillary images in a specific embodiment, and will be explained.

[0028] In an embodiment of the present disclosure, two consecutive frames of pupillograms are used for subsequent contour extraction to improve the accuracy of determining whether the patient is blinking or not.

[0029] In operation 202, contour extraction is performed on each of the two frames of pupil images to obtain two corresponding pupil contours.

[0030] In the embodiment of the present disclosure, the contours of the pupils in the two frames of pupil diagrams are extracted respectively by polar coordinate transformation and shortest path algorithm to obtain two pupil contours.

[0031] Fig. 3 is a schematic diagram of a pupil contour extraction process according to an embodiment of the present disclosure. Referring to Fig. 3, the method of extracting a contour from one of two frames of pupil diagrams is to perform polar coordinate transformation on a normally captured pupil diagram (a) to obtain a transformed pupil diagram (b), perform extraction on the pupil boundary in the transformed pupil diagram (b) based on a shortest path algorithm, obtain a pupil diagram (c) from which the boundary has been extracted, and then perform polar coordinate inverse transformation on the boundary in the pupil diagram (c) from which the boundary has been extracted to obtain a pupil diagram (d) including a pupil contour.

[0032] The pupil contour displayed in pupil diagram (d) is a closed loop contour that surrounds and is a fixed distance from the center of the image at the pupil.

[0033] In an embodiment of the present disclosure, by using polar coordinate transformation and a shortest path algorithm to extract the contours of the pupils in the two frames of pupil diagrams, it is possible to avoid the problem in the related art that when an image binarization method is adopted, the area marked in the binarized image is not necessarily the pupil due to the difficulty in determining the threshold value required for binarization.

[0034] In some embodiments, performing contour extraction on a pupillogram of a frame in operation 202 includes operations A1 to A3.

[0035] In operation A1, a polar coordinate transformation is performed on the pupil diagram to obtain a transformed pupil diagram.

[0036] In operation A2, the boundary of the pupil in the transformed pupillogram is extracted based on a shortest path algorithm.

[0037] In operation A3, an inverse polar coordinate transformation is performed on the boundary to obtain the pupil contour.

[0038] In the embodiment of the present disclosure, the method for extracting a contour from a pupillary image of one frame is described as follows.

[0039] In the embodiment of the present disclosure, the polar coordinate transformation is used to detect closed contours in an image. Referring to FIG. 3, a Cartesian coordinate system xoy is created in the pupil diagram, and the center (x0, y0) of the image is generally selected as the transformation center. Any point (x, y) in the plane of the Cartesian coordinate system xoy is centered at (x0, y0) and corresponds to the polar coordinate (θ, r) in the polar coordinate system by the following calculation formula:

number

[0040] In an embodiment of the present disclosure, the pupil boundary in polar coordinates is found based on a shortest path algorithm, which includes depth- or breadth-first search algorithm, Floyd's algorithm, Dijkstra's algorithm, and Bellman-Ford algorithm.

[0041] In one embodiment, the Dijkstra algorithm is adopted to find the boundary of the pupil in polar coordinates. The steps of adopting the Dijkstra algorithm to find the boundary of the pupil in polar coordinates are as follows:

[0042] In operation 1, one array N and two sets P and Q are maintained in the transformed pupil diagram, where array N is used to store the shortest distance from the starting point to each vertex, set P is used to store the points that have not been traversed, and set Q stores the points that have already been traversed.

[0043] In operation 2, a starting point is selected from set P, the starting point is added to set Q, and is also deleted from set P. Then, the distances to adjacent points of the starting point are added to array N, and the distances to non-adjacent points are represented as infinity.

[0044] In operation 3, one point M closest to set Q (i.e., the point with the smallest edge weight value among all untraversed points connected to all already traversed points) is selected, and the point is added to set Q and deleted from set P.

[0045] In operation 4, a point C adjacent to point M is found, and it is determined whether the distance to reach point C stored in array N is smaller than the distance to reach point C from the starting point via M. If the distance to reach point C stored in array N is smaller than the distance to reach point C from the starting point via M, array N is updated, and if the distance to reach point C stored in array N is equal to or greater than the distance to reach point C from the starting point via M, a point adjacent to the next point M is continuously found, and operation 4 is repeated until all adjacent points of point M have been traversed.

[0046] Until the set P to be traversed becomes empty, that is, the array N constitutes the boundary of the pupil in polar coordinates, the following steps are repeated: "select one point M closest to the set Q (i.e., the point with the smallest edge weight value among all untraversed points connected to all already traversed points), add the point to the set Q, and delete the point from the set P"; and "find a point C adjacent to the point M, and determine whether the distance to reach the point C stored in the array N is smaller than the distance to reach the point C from the starting point via M. If the distance to reach the point C stored in the array N is smaller than the distance to reach the point C from the starting point via M, update the array N. If the distance to reach the point C stored in the array N is equal to or greater than the distance to reach the point C from the starting point via M, continue to find an adjacent point to the next point M, and repeat operation 4 until all adjacent points of the point M have been traversed."

[0047] This is the process of transforming the pupil diagram (b) in FIG. 3 to the pupil diagram (c) after the boundary has been extracted.

[0048] In an embodiment of the present disclosure, the found pupil boundary is transformed from polar coordinates to Cartesian coordinates and corresponds to the coordinates in the Cartesian coordinate system by the following calculation formula:

number

number

[0049] In operation 203, it is determined whether the two pupil contours are similar to a reference contour.

[0050] In the embodiment of the present disclosure, the reference contour is a pupil contour extracted from a pupil reference map, where the pupil reference map and the two consecutive frames of pupil maps to be obtained are taken of the same patient and of the same eye of the patient, and the pupil reference map is a normally taken pupil map in which the pupil of the same patient is not obstructed.

[0051] In the embodiment of the present disclosure, the similarity between the pupil contour and the reference contour is compared to determine the eye state and to achieve better tracking. At the same time, the similarity comparison is not affected by the contour size, but only relates to the shape, so that the change in the size of the pupil, which may be increased or decreased due to the unevenness of the incident light, may be ignored.

[0052] In some embodiments, the reference contour in operation 203 may be obtained by the following operations (operations B1 to B4).

[0053] In operation B1, a pupil reference map, which is a reference map in which the pupil is not obstructed, is obtained.

[0054] In operation B2, a polar coordinate transformation is performed on the pupil reference map to obtain a transformed pupil reference map.

[0055] In operation B3, the boundary of the pupil in the transformed pupil reference map is extracted based on a shortest path algorithm.

[0056] In operation B4, an inverse polar coordinate transformation is performed on the boundary to obtain the reference contour of the pupil.

[0057] In the embodiment of the present disclosure, the operation of extracting the reference contour of the pupil reference map is consistent with the process of extracting contours for one frame of the pupil map in the above operation 202, and reference can be made to operations A1 to A3 in operation 202, and the description will not be repeated here.

[0058] 4 is a schematic diagram showing that the pupil contour and the reference contour are not similar according to an embodiment of the present disclosure. Referring to FIG. 4, the reference contour in the pupil reference image (D) is not similar to either of the two pupil contours (d1) and (d2). In other words, when acquiring two consecutive frames of pupil images, the patient may blink or have eyelids or eyelashes obstructing the pupil, that is, the patient's pupil is obstructed.

[0059] FIG. 5 is a schematic diagram of the pupil contour and the reference contour according to the embodiment of the present disclosure being similar. Referring to FIG. 5, for one of the pupil diagrams (d3), the reference contour in the pupil reference diagram (D) and the pupil contour in the pupil diagram (d3) are similar. In other words, when two consecutive frames of pupil diagrams are obtained, the patient does not blink or the eyelids or eyelashes do not block the pupil, that is, the patient's pupil is not blocked. Wherein, if the distance between the reference contour in the pupil reference diagram (D) and the pupil contour in the pupil diagram is within a preset range, the pupil contour is deemed to be similar to the reference contour, and it can be determined that the patient's pupil is not blocked when the pupil diagram is obtained.

[0060] In some embodiments, operation 203 includes operations C1 through C2.

[0061] In operation C1, the distance between the pupil contour and the reference contour is calculated.

[0062] In operation C2, it is determined whether the pupil contour is similar to the reference contour according to a preset distance range and distance (ie, the distance calculation result obtained by performing operation C1).

[0063] The distance between the disclosed pupil contour and the reference contour is an image moment (Hu moment). The Hu moments of an image are image features that are translation, rotation and scale invariant, and the calculation of the Hu moments includes the calculation of raw moments, the calculation of central moments and the calculation of normalized central moments.

[0064] In one embodiment, the calculation of normalized central moment is adopted to calculate the distance between the pupil contour and the reference contour. The normalized central moment is a linear combination of normalized moments, which can still remain invariant even after the operations such as image rotation, translation, scaling, etc., therefore, we always use the normalized central moment to recognize the image features.

[0065] Calculate the distance between the pupil contour and the reference contour using the following formula:

number

[0066] In an embodiment of the present disclosure, the distance between the pupil contour and the reference contour may be further calculated according to the following formula:

number

[0067] In the embodiment of the present disclosure, the preset distance range is a range of distance values ​​defined by an artificial method, which can be set by oneself according to research needs. When the calculated distance is within the preset distance range, the pupil contour is similar to the reference contour.

[0068] In operation 204, in response to the two pupil contours being similar to the reference contour, a center position shift of one of the two pupil contours relative to the other pupil contour is calculated.

[0069] In an embodiment of the present disclosure, if it is determined that both of the two pupil contours in the pupil diagrams of two consecutive frames are similar to the reference contour, i.e., if both of the pupil diagrams of the two consecutive frames are normal, the central position deviation of one of these two pupil contours relative to the other pupil contour is calculated.

[0070] Calculate the deviation of the center position of one pupil contour from the other pupil contour using the following formula:

number

[0071] In some embodiments, operation 204 includes operation D1 through operation D2.

[0072] In operation D1, for each pupil contour, the center of mass of the pupil contour is obtained.

[0073] In operation D2, the deviation of the center positions is calculated according to the two centers of mass.

[0074] In an embodiment of the present disclosure, the pupil center position is obtained by calculating the center of mass of the contour.

[0075] In an embodiment of the present disclosure, the pupil center position (i.e., the center of mass of the pupil contour) can be obtained by calculating the point in the contour (x A ,y A For example, the method for obtaining the pupil center position is calculated using the following formula:

number

[0076] In the embodiments of the present disclosure, instead of using an ellipse fitting algorithm to fit the pupil center position, the pupil center position is directly calculated, thereby avoiding the error introduced by the ellipse fitting algorithm itself when using the ellipse fitting method, and avoiding the introduction of large errors caused by using a preset shape (e.g., an ellipse) for fitting even if the patient's pupil may already be deformed, and further avoiding the problem of inaccurate pupil marking caused thereby.

[0077] In an embodiment of the present disclosure, an overview of operations 201 to 204 is as follows.

[0078] The photographing method for acquiring the pupil diagram is continuous photographing, and one pupil diagram is acquired for each photographing, that is, the first pupil diagram in any one of two consecutive frames of pupil diagrams in each group in the multiple frame images, and the contour of the first pupil diagram is extracted, and then the contour of the first pupil diagram is compared with the reference contour for similarity. If the contour of the first pupil diagram is similar to the reference contour, photographing is continued, and the next pupil diagram is acquired, that is, the second pupil diagram in any one of two consecutive frames of pupil diagrams in each group in the multiple frame images, and the contour of the second pupil diagram is extracted, and then the contour of the second pupil diagram is compared with the reference contour for similarity. If the pupil contours corresponding to these two pupil diagrams are both similar to the reference contour, the two pupil diagrams are confirmed to be valid, and the deviation of the centers of the two corresponding pupil contours can be calculated.

[0079] In some embodiments, the method further comprises operation 205.

[0080] In operation 205, in response to the two pupil contours being not similar to the reference contour, two consecutive frames of pupil views are reacquired, and the operations of "performing contour extraction for each of the two consecutive frames of pupil views to obtain two corresponding pupil contours" and "determining whether the two pupil contours are similar to the reference contour" are performed, wherein the reacquired two consecutive frames of pupil views are images adjacent to the two consecutive frames of pupil views obtained in operation 201.

[0081] In the embodiment of the present disclosure, if the two pupil contours are not similar to the reference contour, it indicates that the patient blinks or the eyelids or eyelashes block the pupil, i.e., the patient's pupil is blocked. If the patient's pupil is blocked, the results obtained using the subsequent OCTA algorithm will also be inaccurate.

[0082] In an embodiment of the present disclosure, in order to obtain an accurate OCTA image, two consecutive frames of pupil views adjacent to the two consecutive frames of pupil views obtained in operation 201 are reacquired until an accurate OCTA image is obtained, and the following steps are performed: "Contour extraction is performed for each of the reacquired two consecutive frames of pupil views to obtain two corresponding pupil contours" and "Determine whether these two pupil contours are similar to the reference contour."

[0083] In an embodiment of the present disclosure, each subsequent image taken should be run through the method to improve the accuracy of the OCTA image according to the needs of the study.

[0084] By adopting the above technical solutions, in the eye tracking method used in the anterior segment OCTA according to the embodiment of the present disclosure, two consecutive frames of pupil maps are obtained, and then contour extraction is performed for the two frames of pupil maps respectively to obtain two corresponding pupil contours. Then, both of the two pupil contours are compared with a reference contour. If both of the two pupil contours are similar to the reference contour, it is determined that the patient's pupil is not obstructed when the two frames of pupil maps are obtained. At this time, the central position deviation of one of the two pupil contours relative to the other pupil contour is calculated. By calculating the pupil image for subsequent use in the OCTA algorithm, a more accurate OCTA image can be obtained, thereby improving the problem that OCTA in the related art is not suitable for all patients, especially when the patient has poor fixation, frequent blinking, or eye movement, resulting in inaccurate OCTA images, thereby achieving improved suitability of OCTA and elimination of the use of pupil images taken in situations where the patient has poor fixation, frequent blinking, or eye movement, and thus achieving the effect of improving the accuracy of OCTA images.

[0085] Although the above-mentioned embodiments of the method are described as a combination of a series of operations for ease of explanation, those skilled in the art should know that the present disclosure is not limited to the order of operations described, because some operations may be performed in other orders or simultaneously according to the present disclosure. Furthermore, those skilled in the art should know that the embodiments described in the specification belong to preferred embodiments, and such operations and modules are not necessarily required for the present disclosure.

[0086] The above is an introduction to the method embodiment, and the following describes the proposals described in this disclosure through the apparatus embodiment.

[0087] 6 is a structural schematic diagram of an eye tracking device used in an anterior segment OCTA according to an embodiment of the present disclosure. Referring to FIG. 6, the eye tracking device used in the anterior segment OCTA includes an acquisition module 601, an extraction module 602, a determination module 603 and a calculation module 604.

[0088] The acquisition module 601 is configured to acquire two consecutive frames of pupil diagrams, the extraction module 602 is configured to perform contour extraction for each of the two frames of pupil diagrams to obtain two corresponding pupil contours, the determination module 603 is configured to determine whether or not these two pupil contours are similar to a reference contour, and the calculation module 604 is configured to calculate a central position shift of one of the two pupil contours relative to the other pupil contour in response to the two pupil contours being similar to the reference contour.

[0089] In some embodiments, the eye tracking device used in the anterior segment OCTA comprises: The camera further includes a reacquisition module 605 configured to, in response to these two pupil contours being not similar to the reference contour, reacquire two consecutive frames of pupil views and perform the operations of "performing contour extraction for each of the reacquired two consecutive frames of pupil views to obtain two corresponding pupil contours" and "determining whether these two pupil contours are similar to the reference contour", wherein the reacquired two consecutive frames of pupil views are images adjacent to the previously acquired two consecutive frames of pupil views.

[0090] For convenience and conciseness, the operation processes of the modules described above may refer to the corresponding processes in the above-mentioned method embodiments, and will not be described repeatedly here.

[0091] 7 is a structural schematic diagram of an electronic device according to an embodiment of the present disclosure. As shown in FIG. 7, the electronic device 700 shown in FIG. 7 includes a processor 701 and a memory 703. The processor 701 and the memory 703 are connected together. In one embodiment, the electronic device 700 may further include a transceiver 704. In practical applications, the transceiver 704 is not limited to one, and the structure of the electronic device 700 does not limit the embodiment of the present disclosure.

[0092] The processor 701 may be a Central Processing Unit (CPU), a general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in connection with the teachings disclosed in this disclosure. The processor 701 may also be a combination that implements computing functions, including, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0093] The bus 702 may provide a path for transmitting information between the above components. The bus 702 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus 702 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus is represented by only one thick line in FIG. 7, but this does not indicate that there is only one bus or only one type.

[0094] The memory 703 may be, but is not limited to, a Read Only Memory (ROM) or other type of static storage device capable of storing static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an Electrically Erasable Programmable Read Only Memory (EEPROM), a Compact Disc Read Only Memory (CD-ROM) or other optical disk storage, an optical disk storage (including compressed optical disks, laser disks, optical disks, digital versatile optical disks, Blu-ray disks, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be configured to carry or store desired program code in the form of instructions or data structures and accessible by a computer.

[0095] The memory 703 is configured to store the code of an application for carrying out the ideas of the present disclosure and whose execution is controlled by the processor 701. The processor 701 is configured to execute the code of the application stored in the memory 703 in order to realize the contents shown in the method embodiments described above.

[0096] The electronic device 700 includes, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, personal digital assistants (PDA), tablet computers (Portable Android Devices, PAD), portable multimedia players (Portable Media Players, PMP), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital televisions (TV), desktop computers, etc. The electronic device 700 shown in FIG. 7 is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present disclosure.

[0097] An embodiment of the present disclosure provides a computer-readable storage medium having stored thereon a computer program that, when run on a computer, enables the computer to perform corresponding content of the above-described method embodiments. Compared with the related art, in the embodiment of the present disclosure, two consecutive frames of pupil maps are obtained, and then contour extraction is performed on the pupil maps of the two frames respectively to obtain two corresponding pupil contours. Then, both of these two pupil contours are compared with a reference contour. If both of these two pupil contours are similar to the reference contour, it is determined that the patient's pupil is not obstructed when these two frames of pupil maps are obtained. At this time, the central position deviation of one of these two pupil contours relative to the other pupil contour is calculated to be used in the subsequent OCTA algorithm, so that a more accurate OCTA image can be obtained. This can improve the problem that OCTA in the related art is not suitable for all patients, especially when the patient has poor fixation, frequent blinking, or eye movement, resulting in inaccurate OCTA images, thereby achieving the improvement of the suitability of OCTA and the elimination of the use of pupil images obtained in the situation where the patient has poor fixation, frequent blinking, or eye movement, and thus achieving the effect of improving the accuracy of OCTA images.

[0098] Although the steps in the flow diagrams of the drawings are shown in sequence according to the direction of the arrows, these steps are not necessarily performed in sequence according to the order shown by the arrows. Unless otherwise specified in this document, these steps are not limited to a strict order of execution and may be performed in other orders. Furthermore, at least some of the steps in the flow diagrams of the drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages may not necessarily be completed at the same time, but may be performed at different times, and the order of execution may not necessarily proceed sequentially, and may be replaced or alternated with other steps or at least some of the sub-steps or stages of other steps.

Claims

1. acquiring two consecutive frames of pupillograms; extracting a contour from each of the two frames of pupil diagrams to obtain two corresponding pupil contours; determining whether the two pupil contours are similar to a reference contour; and in response to the two pupil contours being similar to the reference contour, calculating a center position shift of one of the two pupil contours relative to the other pupil contour. Eye tracking method used in anterior segment optical coherence tomography angiography (OCTA).

2. Extracting the contour of a pupil diagram in one frame is performing a polar coordinate transformation on the pupil diagram to obtain a transformed pupil diagram; extracting a pupil boundary in the transformed pupillogram based on a shortest path algorithm; and performing an inverse polar transform on the boundary to obtain a corresponding pupil contour. The method of claim 1.

3. Determining whether a pupil contour is similar to the reference contour includes: calculating a distance between the pupil contour and the reference contour; determining whether the pupil contour is similar to the reference contour according to a preset distance range and the distance; The method of claim 1.

4. The step of calculating a displacement of a center position of one of the two pupil contours relative to the other pupil contour includes the steps of: deriving a center of mass of the pupil contour in response to each pupil contour; and calculating the offset of said center position according to the two centers of mass. The method of claim 1.

5. and, in response to the two pupil contours being dissimilar to the reference contour, performing an operation of reacquiring two successive frames of pupil diagrams that are images adjacent to the two successive frames of pupil diagrams, extracting a contour for each of the two successive frames of pupil diagrams, to obtain two corresponding pupil contours, and an operation of determining whether the two pupil contours are similar to the reference contour. The method of claim 1.

6. The reference contour is obtaining a pupil reference map, which is a reference map taken when the pupil is not obstructed; performing polar coordinate transformation on the pupil reference map to obtain a transformed pupil reference map; extracting a pupil boundary in the transformed pupil reference map based on a shortest path algorithm; and performing an inverse polar coordinate transformation on the boundary to obtain a reference pupil contour. The method of claim 1.

7. an acquisition module configured to acquire two consecutive frames of pupillograms; an extraction module configured to extract a contour of each of the two frames of pupil diagrams to obtain two corresponding pupil contours; a determining module configured to determine whether the two pupil contours are similar to a reference contour; a calculation module configured to calculate a center position shift of one of the two pupil contours relative to the other pupil contour in response to the two pupil contours being similar to the reference contour. An eye tracking device used in anterior segment optical coherence tomography angiography (OCTA).

8. and a reacquisition module configured to, in response to the two pupil contours being dissimilar to a reference contour, perform an operation of reacquiring two successive frames of pupil diagrams that are images adjacent to the two successive frames of pupil diagrams, extracting contours for each of the two successive frames of pupil diagrams, to obtain two corresponding pupil contours, and an operation of determining whether the two pupil contours are similar to the reference contour.

8. The apparatus of claim 7.

9. A computer program is stored in a memory and a processor, and when the processor executes the computer program, an eye tracking method for use in an anterior segment optical coherence tomography angiography (OCTA) according to any one of claims 1 to 6 is realized. electronic equipment.

10. A computer program is stored, which, when executed by a processor, realizes the eye tracking method for use in an anterior segment optical coherence tomography angiography (OCTA) according to any one of claims 1 to 6. A computer-readable storage medium.

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