Method and system for monitoring corneal tissue health

Abstract

Disclosed are methods, apparatus, and systems for monitoring the health of corneal tissue, the system including a corneal measurement device configured to measure a first health indicator, the tissue thickness or volume of a region of corneal tissue during a first time period, and a second health indicator, the tissue thickness or volume of the region during a second time period after the first time period, the system further including a processing unit configured to receive the first health indicator and the second health indicator from the corneal measurement device, and generate a health map of the region based on the first health indicator and the second health indicator, the health map indicating a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Application No. 63 / 246,219, filed September 20, 2021, U.S. Provisional Application No. 63 / 276,221, filed November 5, 2021, and U.S. Provisional Application No. 63 / 388,094, filed July 11, 2022, each of which is incorporated by reference herein in its entirety.

[0002] Field The present disclosure relates generally to devices, systems, and methods for health monitoring, such as corneal health monitoring, of an eye. More particularly, the present disclosure relates to devices, systems, and methods for generating a topographical map of the cornea. [Background technology]

[0003] background The cornea is the transparent outer layer at the front of an animal's or human's eye, helping the eye focus light so that animals or humans can see clearly. The cornea can be susceptible to a number of corneal conditions that can interfere with the eye's proper function. For example, abrasions or scratches on the cornea can cause corneal scarring, leading to vision problems. Also, allergic reactions caused by allergens such as pollen can irritate the eye and cause conjunctivitis. Other types of conditions include keratitis or corneal edema, characterized by corneal inflammation or swelling caused by infection or fluid accumulation within the cornea, and keratoconus, a progressive corneal disease in which the outer layer of eye tissue weakens and thins, causing pressure inside the eye to push out the weakened tissue, forming a cone-like shape. This disease progresses over time as the tissue continues to thin and expand when pressure is applied inside the eye. Symptoms include vision impairment and, in more advanced cases, vision loss.

[0004] Some methods for diagnosing keratitis, corneal edema, and keratoconus use corneal topography, which characterizes the surface of the cornea like a mountain. A steep pitch can indicate the risk of keratoconus by identifying the characteristic conical shape of keratoconus, and signs of swelling on corneal topography can identify the potential risk of keratitis or corneal edema. However, identifying early signs of such diseases in an individual based solely on corneal topography measurements can be difficult, as such signs are generally only consistently recognized after the disease has progressed sufficiently. Because every person's eye is unique, a doctor or physician may easily miss early signs of such diseases without performing additional tests or examinations. Summary of the Invention

[0005] Abstract Disclosed are methods, apparatus, and systems for monitoring the health of corneal tissue. A corneal measurement device is used to measure a first health indicator of a region of corneal tissue during a first time period and a second health indicator of the region during a second time period after the first time period. A processing unit can receive the first and second health indicators from the corneal measurement device and automatically generate a health map of the region based on the first and second health indicators. The generated health map can show changes between the first and second health indicators measured in the region of the cornea from the first time period to the second time period, and the health indicator can include one or more of tissue thickness or tissue volume.

[0006] According to one example ("Example 1"), a method for monitoring the health of corneal tissue includes measuring a first health indicator of a region of corneal tissue during a first time period, where the first health indicator is a first tissue thickness of the region of the corneal tissue; measuring a second health indicator of the region during a second time period after the first time period, where the second health indicator is a second tissue thickness of the region; and generating a health map of the region based on the first health indicator and the second health indicator, where the health map shows a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period.

[0007] According to another example ("Example 2"), a method for monitoring the health of corneal tissue includes measuring a first health indicator of a region of corneal tissue during a first time period, where the first health indicator is a first tissue volume of the region; measuring a second health indicator of the region during a second time period after the first time period, where the second health indicator is a second tissue volume of the region; and generating a health map of the region based on the first health indicator and the second health indicator, where the health map shows a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period.

[0008] In addition to Examples 1 or 2, according to one example ("Example 3"), the first health indicator and the second health indicator are measured by obtaining cross-sectional images of the region of corneal tissue at the first time period and the second time period.

[0009] In addition to Example 3, according to one example ("Example 4"), the cross-sectional images of the region of corneal tissue at the first time period and the second time period include (a) a set of first cross-sectional images of the region taken at the first time period, and (b) a set of second cross-sectional images of the region taken at the second time period. The method further includes comparing the first set of cross-sectional images with the second set of cross-sectional images to generate a health map.

[0010] In addition to any of the above examples, according to one example ("Example 5"), the region includes at least one sublayer of the corneal tissue being monitored, and the first health indicator and the second health indicator are associated with at least one sublayer.

[0011] In addition to Example 5, according to one example ("Example 6"), the at least one sublayer includes one or more of an outer sublayer, an inner sublayer, or an intermediate sublayer disposed between the outer sublayer and the inner sublayer.

[0012] In addition to any of the above examples, according to one example ("Example 7"), the method includes calculating a rate of change between the first health indicator and the second health indicator from the first period to the second period based on a health map of the region of the cornea.

[0013] In addition to Example 7, according to one example ("Example 8"), the method further includes determining a predicted health status indicator for the region during a third period after the second period based on the second health status indicator for the region and the rate of change.

[0014] In addition to any of the above examples, according to one example ("Example 9"), the method further includes measuring one or more intermediate health indicators of the region at one or more time points between the first time period and the second time period, and the health map shows continuous changes between the intermediate health indicators.

[0015] In addition to Example 9, according to one example ("Example 10"), the method further includes outputting the continuous changes between the first health status indicator, the second health status indicator, and the intermediate health status indicator as a graph over time.

[0016] In addition to any of the above examples, according to one example ("Example 11"), the method further includes identifying at least one sub-region within the region of the cornea on the health map that exhibits a change in the first health status indicator and the second health status indicator that exceeds a threshold range, and displaying the at least one sub-region on a user interface overlaid on the health map.

[0017] In addition to any one of Examples 1-10, according to one example ("Example 12"), the method further includes determining a diagnosis of the region of corneal tissue based on the health map and a change between the first health indicator and the second health indicator, where the diagnosis is selectable from a list of corneal diseases stored in a memory unit, and displaying the diagnosis and the health map on a user interface.

[0018] In addition to any one of Examples 1 to 10, according to one example ("Example 13"), a health map of the area is displayed as a user interactive map on a user interface, the user interface being configured to receive user input and display additional information corresponding to the received user input.

[0019] In addition to any of the above examples, according to one example ("Example 14"), the health map is a topographical map of the region.

[0020] Further to any of the above examples, according to one example ("Example 15"), the health indicator is measured by optical coherence tomography (OCT).

[0021] In addition to Examples 1 or 2, according to one example ("Example 16"), the method further includes calculating a percent change between the first health indicator of the region and the second health indicator of the region, where the first health indicator is associated with a first period before a corneal implant is implanted and the second health indicator is associated with a second period after the corneal implant is implanted; determining that the percent change is below a predetermined threshold; and displaying a notification on a user interface that the region of the cornea is experiencing tissue loss after the corneal implant is implanted.

[0022] According to one example ("Example 17"), a corneal tissue health monitoring system includes a corneal measurement device configured to measure a first health indicator of a region of corneal tissue during a first time period and a second health indicator of the region during a second time period after the first time period, wherein the first health indicator is a first tissue thickness of the region and the second health indicator is a second tissue thickness of the region, and a processing unit configured to receive the first health indicator and the second health indicator from the corneal measurement device and generate a health map of the region based on the first health indicator and the second health indicator, wherein the health map indicates a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period.

[0023] According to one example ("Example 18"), a corneal tissue health monitoring system includes a corneal measurement device configured to measure a first health indicator of a region of corneal tissue during a first time period and a second health indicator of the region during a second time period after the first time period, wherein the first health indicator is a first tissue volume of the region and the second health indicator is a second tissue volume of the region, and a processing unit configured to receive the first health indicator and the second health indicator from the corneal measurement device and generate a health map of the region based on the first health indicator and the second health indicator, wherein the health map indicates a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period.

[0024] In addition to Examples 17 or 18, according to one example ("Example 19"), the first health indicator and the second health indicator are measured by obtaining cross-sectional images of the area of ​​corneal tissue during the first period and the second period.

[0025] In addition to Example 19, according to one example ("Example 20"), the cross-sectional images of the region of corneal tissue at the first time period and the second time period include (a) a set of first cross-sectional images of the region taken at the first time period, and (b) a set of second cross-sectional images of the region taken at the second time period. A processing unit compares the first set of cross-sectional images with the second set of cross-sectional images to generate a health map.

[0026] In addition to any one of Examples 17-20, according to one example ("Example 21"), the region includes at least one sublayer of the corneal tissue being monitored, and the first health indicator and the second health indicator are associated with the at least one sublayer.

[0027] In addition to Example 21, according to one example ("Example 22"), the at least one sublayer includes one or more of an outer sublayer, an inner sublayer, or an intermediate sublayer disposed between the outer sublayer and the inner sublayer.

[0028] In addition to any of Examples 17-22, according to one example ("Example 23"), the processing unit is further configured to calculate a rate of change between the first health status indicator and the second health status indicator from the first time period to the second time period based on a health map of the region.

[0029] In addition to Example 23, according to one example ("Example 24"), the processing unit is further configured to determine a predicted health status indicator of the region during a third period after the second period based on the second health status indicator of the region and the rate of change.

[0030] In addition to any one of Examples 17 to 24, according to one example ("Example 25"), the corneal measurement device is further configured to measure one or more intermediate health indicators of the area between the first period and the second period, wherein the health map indicates continuous changes between the intermediate health indicators.

[0031] In addition to Example 25, according to one example ("Example 26"), the processing unit is further configured to output continuous changes between the first health status index, the second health status index, and the intermediate health status index as a graph over time.

[0032] Further to any one of Examples 17 to 26, according to one example ("Example 27"), the processing unit is further configured to identify on the health map the location of at least one subregion within the region of the cornea that exhibits changes in the first health indicator and the second health indicator that exceed a threshold range, and the corneal tissue health monitoring system further includes a user interface configured to display the at least one subregion overlaid on the health map.

[0033] In addition to any one of Examples 17-26, according to one example ("Example 28"), the corneal tissue health monitoring system includes a memory unit configured to store a list of corneal diseases. The processing unit is further configured to determine a diagnosis for the region of corneal tissue based on the health map and a change between the first health indicator and the second health indicator, the diagnosis being selectable from the list of corneal diseases stored in the memory unit. The corneal tissue health monitoring system further includes a user interface configured to display the diagnosis and the health map.

[0034] In addition to Example 28, according to one example ("Example 29"), the corneal tissue health monitoring system includes a user interface configured to display a health map of the area as a user interactive map, receive user input, and display additional information corresponding to the received user input.

[0035] In addition to Example 29, according to one example ("Example 30"), the user interface is further configured to open a new window displaying additional information in response to detecting a user input, the additional information being a cross-sectional image of the area selected by the user on the user interactive map.

[0036] In addition to any one of Examples 17-30, according to one example ("Example 31"), the health map is a topographical map of the region.

[0037] In addition to any of Examples 17-31, according to one example ("Example 32"), the health indicator is measured by optical coherence tomography (OCT).

[0038] In addition to Examples 17 or 18, according to one example ("Example 33"), the corneal tissue health monitoring system further includes a user interface. The processing unit is configured to calculate a percent change between a first health indicator of the region and a second health indicator of the region, where the first health indicator is associated with a first time period before a corneal implant is implanted and the second health indicator is associated with a second time period after the corneal implant is implanted, determine that the percent change is below a predetermined threshold, and display a notification on the user interface that the region of the cornea is experiencing tissue loss after the corneal implant.

[0039] The foregoing examples are merely illustrative and should not be construed to limit or narrow the scope of the inventive concepts otherwise provided by this disclosure. While multiple examples are disclosed, still other embodiments will become apparent to those skilled in the art from the following detailed description, which shows and describes illustrative examples. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature and not as restrictive. [Brief explanation of the drawings]

[0040] BRIEF DESCRIPTION OF THE DRAWINGS This patent or application file references and claims priority to U.S. Provisional Application No. 63 / 388,094, filed July 11, 2022. This provisional application contains at least one drawing executed in color.

[0041] The accompanying drawings are included to provide a further understanding of the disclosure, and are incorporated in and constitute a part of this specification, illustrate embodiments and, together with the description, serve to explain the principles of the disclosure.

[0042] [Figure 1] FIG. 1 is a schematic diagram of a corneal health monitoring system implementing a network of connected electronic devices according to embodiments disclosed herein.

[0043] [Figure 2] FIG. 2 is a schematic diagram of one of the electronic devices used to monitor corneal health according to embodiments disclosed herein.

[0044] [Figure 3] FIG. 3 is a cross-sectional view of an eye focusing on the area scanned by the corneal tissue and health measurement device monitored by the system according to an embodiment disclosed herein.

[0045] [Figure 4A] FIG. 4A is a partial cross-sectional view of an eye focusing on corneal tissue surrounding a corneal implant as monitored by a system according to embodiments disclosed herein.

[0046] [Figure 4B] FIG. 4B is a partial cross-sectional view of an eye focusing on the corneal tissue surrounding the post-LASIK surgery area as monitored by a system according to embodiments disclosed herein.

[0047] [Figure 5] FIG. 5 is a health map generated by a corneal health monitoring system according to embodiments disclosed herein.

[0048] [Figure 6] FIG. 6 is an illustration of a user interface and display monitor implemented in one of the electronic devices used for corneal health monitoring according to embodiments disclosed herein.

[0049] [Figure 7] FIG. 7 is a comparative graph of sample data relating to corneal health monitored by a system according to embodiments disclosed herein.

[0050] [Figure 8]FIG. 8 is a flowchart of a method for monitoring corneal health by generating a health map according to embodiments disclosed herein.

[0051] [Figure 9] FIG. 9 is a flowchart of a method for monitoring corneal health by predicting future states of corneal health according to embodiments disclosed herein.

[0052] [Figure 10] FIG. 10 is a flowchart of a method for monitoring corneal health by taking multiple consecutive measurements of an output health indicator according to embodiments disclosed herein.

[0053] [Figures 11A-F] 11A-11F are health maps generated by a corneal health monitoring system at different time periods after a corneal implant procedure, according to embodiments disclosed herein.

[0054] [Figure 11G] FIG. 11G is a graph based on FIGS. 11A to 11F showing changes in corneal tissue volume after corneal implantation treatment.

[0055] [Figures 12A-F] 12A-12F are health maps generated by a corneal health monitoring system at different time periods after a corneal implant procedure, according to embodiments disclosed herein.

[0056] [Figure 12G] FIG. 12G is a graph showing the change in corneal tissue volume after the corneal implant procedure based on FIGS. 12A to 12F.

[0057] [Figures 13A-F]13A-13F are health maps generated by a corneal health monitoring system at different time periods after a corneal implant procedure, according to embodiments disclosed herein.

[0058] [Figure 13G] FIG. 13G is a graph showing the change in corneal tissue volume after the corneal implant procedure based on FIGS. 13A to 13F.

[0059] [Figure 14] FIG. 14 is a comparative graph of the changes in corneal tissue volume in FIGS. 11G, 12G, and 13G.

[0060] [Figure 15] FIG. 15 is a flowchart of a method for monitoring corneal health and detecting tissue volume loss after implantation of various corneal implants according to embodiments disclosed herein.

[0061] [Figure 16] 16 is a cross-sectional image of the cornea of ​​an eye showing sublayers that can be monitored in accordance with embodiments disclosed herein; and

[0062] [Figure 17] FIG. 17 is a flowchart of a method for monitoring corneal health and detecting tissue volume loss after implantation of various corneal implants according to embodiments disclosed herein. DETAILED DESCRIPTION OF THE INVENTION

[0063] Detailed Description Definitions and Terminology This disclosure is not intended to be construed in a limiting sense. For example, the terms used in this application should be read broadly in the context of the meanings ascribed to such terms by experts in the field.

[0064] With respect to the term imprecision, the terms "about" and "approximately" may be used interchangeably to refer to measurements that include the stated measurement and also measurements that are reasonably close to the stated measurement. A measurement that is reasonably close to the stated measurement deviates from the stated measurement by a reasonably small amount, as understood and easily ascertained by one of ordinary skill in the relevant art. Such deviations may result, for example, from measurement error, differences in calibration of measuring and / or manufacturing equipment, human error in reading and / or setting measurements, fine-tuning made to optimize performance and / or structural parameters given differences in measurements associated with other components, specific implementation scenarios, imprecise adjustment and / or manipulation of objects by humans or machines, etc. If it is determined that the value of such a reasonably small difference would not be easily ascertainable by one of ordinary skill in the relevant art, the terms "about" and "approximately" may be understood to mean plus or minus 10% of the stated value.

[0065] The term "thickness" of an object is used to refer to the distance measured between the outer and inner surfaces of the object. The object can be a cornea or a portion of a cornea, as described herein.

[0066] The term "volume" of an object is used to refer to the amount of space that an object or a portion of an object occupies. The object can be a portion of a cornea as described herein, and the volume of the cornea is the total volume that it occupies within a measurement area when viewed from a particular angle.

[0067] The term "opacity" of the cornea is used to refer to the amount or percentage of light observed to pass through the cornea or a portion of the cornea from one side of the cornea to the other.

[0068] The term "density" of the cornea is used to refer to the density of corneal endothelial cells in the particular area being measured. If endothelial cell density falls below a critical lower limit, corneal function may be irreversibly impaired, and endothelial cell density is in some cases related to corneal opacity.

[0069] Description of Various Embodiments FIG. 1 illustrates a corneal tissue health monitoring system 100, according to some embodiments. System 100 includes a health measurement device 102 used to measure the corneal health of person X, also referred to herein as the patient. System 100 also includes a monitoring device 104 operatively coupled to device 102 and controlling and / or receiving data from device 102 for evaluation or review by person A, who may be the patient's physician or doctor as disclosed herein, or the patient themselves. Monitoring device 104 is further connected to a network 106, such as a cloud computing network or an internet communications network, operatively connecting monitoring device 104 to at least one of a remote server 108, a mobile device 110 accessible by another person B, or another monitoring device 112 accessible by another person C. Any one of these monitoring devices 104 and 112 or mobile device 110 may be referred to as a user terminal. Person B and Person C can be the patient, the doctor / physician, or other persons authorized to access data regarding the health of Person X's cornea, such as the patient's family members, specialists contacted by the doctor to obtain a second opinion on the diagnosis, or other authorized persons or entities.

[0070] In the examples disclosed herein, the device 102 can be any suitable device for measuring any suitable indicator of corneal health. For example, the device 102 can be an optical coherence tomography (OCT) device that performs OCT imaging by taking pictures of the eye using light, in a manner similar to ultrasound, which uses sound to create an image. OCT imaging creates image "slices" of the eye by sweeping the eye 360 ​​degrees, centered on the pupil. The tissue areas in each slice are combined to create thickness or volume measurements, and physicians can compare these values ​​at each patient visit to monitor tissue volume over time. The rate of this tissue thinning is believed to be a key factor in establishing a diagnosis and treatment for keratoconus. Alternatively, in other examples, the device 102 can be any suitable confocal imaging device, laser scanning microscope device, or pachymetry device capable of providing data suitable for analysis, as described further herein, for example.

[0071] In the system 100, data acquired using the apparatus 102 can be analyzed using one or more of the monitoring device 104, the server 108, the mobile device 110, or the additional monitoring device 112, each of which can include at least one processing unit capable of performing data processing or analysis of the acquired data.

[0072] 2 illustrates a monitoring device 104 capable of performing such data processing and analysis, according to some embodiments. The device 104 includes a processing unit 200 coupled to a memory unit 202, a display and / or user interface 204, an input module or receiver 206, and an output module or transmitter 208. The processing unit 200 includes a measurement device control unit 210 and an image generation or processing unit 212. The input module 206 and the output module 208 can be connected to the measurement device 102 and to a network 106 via which data analysis can be distributed and other information can be stored and / or communicated.

[0073] The device 102 is controlled by a user using a user interface 204 and a control unit 210. In particular, the user can input commands to perform corneal tissue health monitoring, which are received by the control unit 210 and then converted into appropriate control signals that are output to the device 102 via an output module 208 to operate the device 102. In return, the input module 206 receives data generated by the device 102, which is processed using an image generation or processing unit 212, after which the resulting images can be displayed for the user to review on the user interface 204. The user interface 204 can include a display device, such as a display monitor or a touch screen that operates as both a user interface and a display.

[0074] A user uses device 102 to take measurements of the health indicators of person X's cornea over a period of time, so that device 102 can obtain health indicators for different periods of time, such as multiple days, weeks, or months. Thus, each measurement of the health indicator is time-stamped with the day and, in some instances, the specific time the measurement was taken. In some instances, device 102 is installed in person X's home rather than in a clinic, so that person X can take frequent measurements of their cornea from the comfort of their home or other location. Analysis of the measurements can then be transmitted from monitoring device 104 (which in this case can be person X's personal computer (e.g., a PDA, desktop, laptop, tablet, or other device)) to remote monitoring device 112 installed in the clinic. A doctor or person C can then review the results without having to visit person X's home, have person X visit the clinic, or otherwise be near monitoring device 104. In some instances, person A can be the same as person X.

[0075] The memory unit 202 can be any suitable type of non-transitory computer-readable medium, such as random access memory, read-only memory, flash memory, or other medium, and can store data generated by the device 102. The memory unit 202 can also store program code that, when executed by the processing unit 200, causes the image generation or processing unit 212 to generate a health map based on the data stored in the memory unit 202. The health map shows changes in health indicators from a first time period to a second time period subsequent to the first time period, where the changes relate to the same region or area of ​​the cornea measured. Thus, a health map requires at least two measurements of the same region or area of ​​the cornea during at least two different time periods to effectively show changes between at least two health indicators measured during different time periods. For the avoidance of doubt, as used herein, the phrase "same region or area" is intended to indicate substantial overlap of sample areas from which data are acquired, but is not intended to require absolute overlap of the sample areas.

[0076] In some examples, the analysis is performed using artificial intelligence (AI), or more specifically, machine learning infrastructure such as artificial neural networks (ANNs), among others, to train and operate an AI-based segmentation model, where the model segments relevant portions of the eye image and determines which portions to focus on when taking measurements. For example, proprietary calculations can be used to determine the area to be covered, and the area is distributed online, for example, through a web application developed for such purposes. The web application can be installed and operated on any suitable electronic device capable of performing AI-based analysis. The AI-based segmentation model can be trained using a series of scan images, such as OCT scans and thickness / volume measurements, until the algorithm learns how to automatically segment the relevant portions. This algorithm is then subsequently used on new image sets, such as OCT image data, from which it outputs tissue thickness / volume measurements for automatic tissue thickness / volume estimation.

[0077] In some examples implementing AI-powered analysis, machine learning infrastructure can facilitate diagnosis of corneal tissue based on OCT image data. For example, based on previously provided OCT image data, a machine learning model algorithm can be trained to recognize patterns in the training data regarding corneal tissue conditions, such as high-risk areas of the cornea for keratoconus or corneal edema. The algorithm can implement a feedback loop that captures how a user (e.g., a physician reviewing the AI-generated results and diagnoses) reacts to or engages with the model's output. If the user notices an error in the machine-generated diagnosis, the feedback loop facilitates correcting such errors in future model iterations as part of an optimization process to improve the accuracy of the machine learning model. Thus, in some examples, the machine learning model can generate a diagnosis on behalf of a physician or reviewer, such as Person A. In some examples, the machine learning model can further output a suggested treatment plan based on the diagnosis, for example, by sending a notification to the user or by outputting instructions regarding a treatment plan to be implemented by an automated corneal treatment device.

[0078] FIG. 3 illustrates an example of an eye region 300 targeted by an AI-enabled segmentation model according to embodiments disclosed herein. Region 300 is defined by a predetermined distance, e.g., approximately 0.25 mm to 1 mm, from the center of the iris, more specifically from the center of the pupil, such that cross-sectional images of the eye (or at least a portion thereof) are taken 360 degrees about a centerline defined by the center of the pupil and the center of the cornea. This distance may be increased or decreased depending on the particular region of the cornea being monitored. As shown in FIG. 3, when monitoring the entire cornea, the distance is adjusted to at least cover the distance between the positions where the cornea protrudes anteriorly relative to the iris.

[0079] FIG. 4A shows another example of an eye region 300 targeted for segmentation. In this example, the purpose of monitoring the cornea is to determine corneal abnormalities caused by the placement of a corneal implant 400 within the cornea. The implant 400 can be placed by making an incision in the corneal tissue to form a "pocket" into which a portion of the implant 400 is inserted to hold the implant in place. In this case, the tissue surrounding the implant, i.e., the support portion 402 of the cornea (also called the anterior tissue), is of primary importance. The contact area 404 between the support portion 402 of the cornea and the implant 400, as marked by the circle, is also monitored. The support portion 402 is defined by a support width "Wsupport" and a support thickness "Tsupport," where the support width Wsupport determines the minimum distance of the monitoring region 300 and the support thickness Tsupport will be monitored using the measurement device 102. The tissue volume of the support portion 402 can be calculated based on the measured support width Wsupport and support thickness Tsupport. The support thickness Tsupport can be, for example, about 0.1 mm to 0.5 mm, depending on, for example, whether tissue weakening or inflammation is present. The support width Wsupport can be, for example, about 0.5 mm to 1.5 mm, depending on the range the physician decides to monitor for the corneal tissue surrounding the implant. It should be understood that any other suitable ranges for support width and thickness can be implemented.

[0080] The implant 400 can be positioned relative to the outer and inner surfaces 406 and 408 of the cornea such that the outer surface of the implant 400 is relatively flush with the outer and inner surfaces 406 and 408 of the cornea. The implant 400 can be any implantable, metastable device suitable for the cornea, such that the material is biointegrated or biocompatible, causes low inflammation to the surrounding corneal tissue, and promotes good epithelial health within the tissue to prevent infection. In some examples, the implant is made from a biocompatible material, including, but not limited to, a fluoropolymer, such as polytetrafluoroethylene (PTFE) polymer or expanded polytetrafluoroethylene (ePTFE) polymer. In some examples, biocompatible materials used for the implant can include, but are not limited to, polyethylene and expanded polyethylene.

[0081] In certain instances, additional components, such as sutures, can be formed from materials such as, but not limited to, polyester, silicone, urethane, polyethylene terephthalate, another biocompatible polymer, or a combination thereof. In some instances, bioresorbable or bioabsorbable materials, such as bioresorbable or bioabsorbable polymers, can be used for the implant and / or sutures. In some instances, the sutures can include Dacron, polyolefin, carboxymethyl cellulose fabric, polyurethane, or other woven, nonwoven, or film elastomers. Monitoring devices such as those described above can be used as diagnostic aids to diagnose the condition of corneal tissue after implant placement and / or to track the health of the tissue surrounding the implant over time, such as during the life of the implant.

[0082] 4B shows another example of an eye region 300 targeted for segmentation. In this example, the purpose of monitoring the cornea is to determine corneal abnormalities resulting from LASIK surgery performed in the cornea, as indicated by incision marks 410 extending from the outer surface 406 toward the inner surface 408 of the cornea. Thus, region 300 can be of a size sufficient to monitor the condition of the corneal tissue before, during, and after LASIK surgery, as well as the condition of the corneal tissue in the area most likely to be affected by the surgery.

[0083] 5 illustrates a corneal tissue data map 500, according to some embodiments. Corneal tissue data map 500 can be a health map showing changes in corneal tissue thickness as a function of time, allowing a physician to monitor the health of person X's cornea over a period of time and determine whether any abnormalities are observed, or, in the case of post-surgical or post-procedural monitoring, determine the progress and effectiveness of treatment. As shown, data map 500 has a diameter "D" associated with a predetermined distance of region 300 and a center "C" located at the center of the pupil (or elsewhere on the cornea, if preferred by the physician). Data map 500 can be a topographical map of the region of corneal tissue being monitored.

[0084] The data map 500 includes a legend defining the percent change observed in corneal tissue thickness from a first measurement to a second measurement, the two measurements being taken at specified intervals, such as one month. In some examples, the data map may be color-coded so that each color represents a different percent value. For example, red is 50% of the tissue thickness between the two measurements (i.e., tissue thickness has decreased or thinned), blue is 150% of the tissue thickness (i.e., tissue thickness has increased or expanded), and other intermediate colors, such as orange, yellow, green, etc., define different values ​​in between.

[0085] According to some examples, in the illustrated black-and-white data map 500, the shaded region (506) defines the region of greatest tissue thickness increase, i.e., at least approximately 130% of the original thickness. The region (508) with diagonal hatching from lower left to upper right defines the region of lesser tissue thickness increase, i.e., approximately 110%-130% of the original thickness. The white region (510) defines the region of least tissue thickness increase or decrease, i.e., approximately 90%-110% of the original thickness. The region (512) with diagonal hatching from upper left to lower right defines the region of greater tissue thickness decrease, i.e., approximately 70%-90% of the original thickness. The darker shaded region (514) defines the region of greatest tissue thickness decrease, i.e., approximately 70% or less of the original thickness.

[0086] In the illustrated example, it can be seen that one subregion 502 includes portions that have experienced a greater percent increase in tissue thickness. For example, as shown, the final tissue thickness is approximately 130%-150% of the initial tissue thickness, while the thickness of another subregion 504 remains relatively the same (approximately 100%), or in some portions may decrease to approximately 80% of the initial thickness (as observed in the region of diagonal hatching from upper left to lower right), or even to approximately 50% of the initial thickness (as observed in the darker shaded region).

[0087] In some examples, the image generation or processing unit 212 can analyze the generated image or data map 500 to determine portions or subregions within the data map that have a higher risk of developing corneal disease. For example, the processing unit 212 can flag each subregion on the data map 500 where the percent change is above an upper threshold (“dark points”) or below a lower threshold (“light points”). That is, if the thickness of a subregion increases by more than a threshold, such as about 130%, 140%, or 150%, or any value therebetween, compared to the initial thickness, the processing unit 212 can determine that there are one or more thick points and that there is a high risk of developing keratitis or corneal edema. If the thickness of a subregion decreases by less than a threshold, such as about 70%, 60%, or 50%, compared to the initial thickness, or any value therebetween, the processing unit 212 can determine that there are one or more thin points and that there is a high risk of keratitis or corneal edema.

[0088] Processing unit 212 may then display high-risk subregions on data map 500 on a user interface or overlay a marker on data map 500 to indicate such subregions. In some examples, processing unit 212 may also provide a diagnosis of the corneal tissue based on an analysis of data map 500, in which case processing unit 212 may select a diagnosis from a list of corneal diseases stored in the memory unit and display the selected diagnosis for user review.

[0089] 6 illustrates an exemplary monitoring device 104 that includes not only the processing unit 200, but also a separate display 204A (i.e., display monitor) and user interface 204B (i.e., keyboard). The keyboard 204B allows a user to interact with the data map 500, in this case a user-interactive map shown on the display monitor 204A. Using the keyboard 204B, a user can select a subregion 602 within the data map 500, and in response, the processing unit 200 can cause the display monitor 204A to show or display additional information 600 that can be overlaid on the data map 500 or can be shown in a new pop-up window on or near the data map 500. The additional information 600 can be any suitable information regarding the user-selected subregion 602, such as an original cross-sectional image of the region of corneal tissue generated by the apparatus 102, a graph showing the change in thickness of the subregion as a function of time, a possible diagnosis generated by the system 100 as described herein, etc. The additional information 600 may be stored in the memory unit 202 until the processing unit 200, or more specifically the image generation or processing unit 212, decides to display the information for user review.

[0090] In some examples, the data map 500 may also include a time adjustment feature 604, such as a scroll bar or pull-down menu, or any other suitable user input feature, for the user to adjust the time period of interest. For example, while the data map 500 of FIG. 6 shows the change in corneal tissue thickness from a first thickness measured at time t0 to a second thickness measured at time t3, the user may use the time adjustment feature 604 to select time t2 or time t1 instead of time t3. In this case, a different data map is displayed showing the change in corneal tissue thickness from t0 to the selected one of t2 or t1. The health indicator, such as tissue thickness or volume measured at time t0, is considered the baseline indicator from which change is calculated. This may be, for example, the oldest measurement taken by person X or a time selected by a physician to begin monitoring person X's corneal health.

[0091] 7 shows a comparative graph 700 of six separately collected sample data, which may be displayed on the display monitor 204A as additional information 600 in response to user input. In some examples, the system 100 may operably connect multiple health measurement devices 102 to the network 106, such that a physician may access any one or more of the data obtained from multiple devices 102 from their monitoring devices 104, 110, or 112 to determine changes in tissue volume (e.g., mm) over a period of time. 3 (measured at 12, 24, 36, 38, 40, 42, 44, 45, 46, 47, 48, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 15

[0092] FIG. 8 illustrates an exemplary method 800 used by system 100 to obtain a health map for display to a user. In step 802, a first health index of a region of corneal tissue is measured during a first time period. In step 804, a second health index of the same region of corneal tissue is measured during a second time period. In step 806, a health map of the region is generated, the health map showing the change from the first health index to the second health index. As disclosed herein, generation of the health map can be performed using any suitable algorithm, including, but not limited to, an AI-enabled segmentation model that creates a topographical map of the region of corneal tissue by comparing the difference between the first health index and the second health index as a function of time. In step 808, the health map is displayed on a user terminal, such as a display monitor of a user monitoring device or mobile device.

[0093] 9 illustrates an exemplary method 900 used by system 100 to utilize health measurement information to provide a prediction regarding the health of the cornea. In step 902, which follows step 806 of method 800, system 100 calculates a rate of change from a first health index to a second health index. Based on this rate of change, system 100 calculates a predicted health index for the same region of corneal tissue during a third time period after both the first and second time periods during which measurements were taken. Thus, by calculating the rate of change from past measurements, system 100 can predict future health index measurements. This prediction can be displayed as additional information 600 to help a user, who may be a physician, for example, better understand the severity of the disease.

[0094] 10 illustrates an exemplary method 1000 used by system 100 to perform more than two measurements for health map generation and how additional measurement information may be utilized. Following step 802, where a first health indicator is measured, step 1002 may measure one or more intermediate health indicators in the same region between the first and second time periods. Step 1002 is then followed by step 804, where a second health indicator is measured, also referred to as a final health indicator because it is the last indicator measured in the series of indicators beginning with the first indicator in step 802. Thus, the series of data related to the indicators may indicate the progression of corneal tissue disease, and in some instances, diseased or potentially diseased areas may be visually marked for review by a physician.

[0095] After a health map is generated based on the first health status index and the final health status index in step 806, the continuous changes between the first health status index, the intermediate health status index, and the final (or second) health status index are output as a graph against time in step 1004. That is, each measurement of the health status index is plotted on a graph to show how the health status index varies from one period to another as a function of time.

[0096] With respect to the steps of methods 800, 900, and 1000, it should be understood that the health indicator can be any one of tissue thickness, tissue volume, or tissue opacity (or density), another indicator, or any combination of the aforementioned indicators, of the region of the cornea being measured. In some examples, the health indicator is measured by acquiring cross-sectional images of the region of corneal tissue at different time periods. The cross-sectional images can include a first set of cross-sectional images of the region of corneal tissue taken at a first time period and a second set of cross-sectional images of the same region taken at a second time period after the first time period. The first and second sets are then compared to each other, and changes from the first set to the second set are determined, followed by generating a health map.

[0097] In some examples, analysis and / or diagnosis may be performed using a single set of health indicator measurements taken over a single period of time. That is, instead of comparing two sets of cross-sectional images, the system may be able to determine dark and light spots from only a single set of cross-sectional images. For example, if the thickness of the corneal tissue is outside of a typical range of thicknesses considered healthy, the system may provide an instantaneous or near-instantaneous alert to a physician, informing them that person X's corneal tissue may have a problem. The system may further provide a diagnosis based on the single set of cross-sectional images, or may take measurements over a subsequent period of time to determine whether the risk of disease still exists.

[0098] Health maps generated using any of the aforementioned methods and systems can be used to diagnose, monitor, and evaluate the effectiveness of treatment. Clinicians can better determine effectiveness by reviewing the health map, which combines changes in corneal tissue thickness or volume with topographic imaging. This provides an additional visual aid to diagnosis, eliminating the need to manually track scanned tissue volumes from each patient visit to the clinic and comparing current tissue status with previous tissue status provided by one or more previous scans. Automating the generation of such health maps can reduce the margin of error in both the frequency and regularity of image data for review and manual calculations.

[0099] In some examples, user or person X utilizes a home OCT device (i.e., apparatus 102) to image the cornea as frequently as needed, rather than having to travel to a doctor's office to use the OCT equipment and device. Reducing multiple office visits may make OCT scans more accessible to patients, particularly those with more severe symptoms of corneal disease and limited mobility. This increased accessibility to OCT devices facilitates the generation of more timely patient scan data and speeds analysis of treatment effectiveness, as data analysis may be less frequent if the patient is unable to travel frequently. Faster or earlier analysis of the effectiveness or success of treatment may allow the physician to make adjustments as needed if the treatment is not deemed successful.

[0100] The images can be analyzed using person X's monitoring device 104, or can be anonymized and sent to a cloud network 106 for analysis, where the analysis can be performed by, for example, a server 108. An algorithm executed by the server 108 can import and convert the OCT images into a manageable dataset to measure the volume of corneal tissue over time. Each volume calculation can be compared to a baseline tissue volume to calculate the change in volume over time. The analysis can be plotted in both a topographical map and in graphical form for review by a physician on a digital interface (i.e., any one of devices 104, 110, and 112). In some examples, the volume measurements are analyzed with respect to the difference between the corneal orientation angle and the OCT coordinate system.

[0101] As known in the art, OCT devices form OCT images one row at a time using infrared light that passes through the surface of a sample and reflects off materials within the sample. OCT devices use interference principles to determine the depth from which infrared light photons are reflected within the sample. The depth of the photon reflections is measured, aggregated into image rows, and by scanning the beam laterally, adjacent rows are aggregated into a 2D image. This 2D image represents a cross-sectional image of the scanned sample. By aggregating and compiling multiple 2D images acquired in this manner, OCT devices can construct a 3D representation of the sample. Unlike ultrasound-based scanning devices, which can see several centimeters into tissue with millimeter-level resolution, OCT devices can see several millimeters into tissue with micrometer-level resolution, making OCT the preferred method for scanning corneal tissue for abnormalities. However, other known scanning methods can be used to achieve similar results.

[0102] In some instances, as further disclosed herein, the interface allows physicians to click on focal areas on the topographic map to review the raw (or pre-analysis) OCT image data and validate the algorithmic analysis, providing physicians with greater confidence in the analysis. Thus, the system 100 provides physicians with a diagnostic tool to better inform the effectiveness of treatments and therapies. This improved patient monitoring allows physicians to tailor treatments, quickly understand effectiveness, adjust treatments or therapies as needed without requiring additional office visits, and create additional telehealth opportunities for high-risk patients. Additionally, the cloud nature of the software allows companies using the system 100 to collect patient-consented data to generate insights that can inform software improvements, future product offerings, and quantitative data on treatment outcomes.

[0103] Health maps are representations of corneal tissue thickness and corneal tissue volume that can be generated according to the techniques described above with respect to Figures 5-7. These health map representations of corneal thickness or volume can be presented as color images, with colors representing different values ​​of thickness or volume at various locations around the cornea, or as black-and-white or grayscale images, as shown in Figures 11A-11F, 12A-12F, and 13A-13F, where lighter areas represent areas where tissue thickness has changed less (i.e., remaining at about 20% of its original thickness from 100%). As can be appreciated, the colored health map representations can also be presented in other formats, such as black-and-white, where the various colors are alternatively represented by appropriate imagery that conveys meaning in the black-and-white image, such as by using cross-hatching or stippling as shown in Figure 5. It will also be appreciated that another format may be a numerical format in which the thickness or volume numerical value is represented by small numbers displayed on and around the health map image, whereby the thickness and volume data may be represented similarly to a map in which ocean depth values ​​are distributed around an image of a body of water to show the depth of the ocean at various locations.

[0104] 11A-11F show health maps illustrating the progression of tissue inflammation or tissue loss in a region of the cornea following implantation of a corneal implant, such as corneal implant 400 shown in FIG. 4A. Tissue thickness is measured near the contact portion (e.g., contact portion 404) where the corneal tissue contacts the implant (e.g., support portion 402), thus forming a ring having a predetermined width, as shown in the figures.

[0105] When a corneal implant is applied to a subject's cornea, inflammation and thickening of the tissue surrounding the implant may occur for a period of time following the procedure. Once the implant is safely incorporated into the subject's cornea, the inflammation (and tissue thickness) is expected to subside and stabilize over time, resulting in a decrease in tissue volume or thickness, returning the tissue to approximately the same volume and thickness that existed before the implant was applied. However, in some cases, the tissue volume or thickness of the corneal tissue may further decrease beyond its original volume or thickness, indicating a serious medical condition that may require urgent medical attention. In such cases, the loss of corneal tissue volume or thickness may be the result of a defect in the implant or may be due to a medical condition in the subject that, if left untreated, could permanently damage the cornea. Therefore, monitoring the volume or thickness of corneal tissue following an implant procedure is important in preventing or mitigating problems that may be caused or exacerbated by the implant procedure or the presence of the implant, or problems that may be caused by unknown external factors, and in assisting the physician or doctor in determining whether the implant or unknown external factors are factors affecting tissue loss.

[0106] In the figures shown, FIG. 11A is a health map generated one month after implantation, FIG. 11B is a health map generated two months after implantation, FIG. 11C is a health map generated three months after implantation, FIG. 11D is a health map generated four months after implantation, FIG. 11E is a health map generated five months after implantation, and FIG. 11F is a health map generated six months after implantation. While the health maps are generated in monthly increments, it should be understood that any other shorter or longer increments may be used as appropriate for the procedure. According to the provided legend, in some examples where the health map is generated in color, red areas may indicate substantial tissue loss at approximately 50% of the original tissue thickness, green areas may indicate relatively small changes in tissue thickness (approximately 100% of the original tissue thickness), and blue areas may indicate substantial tissue inflammation at approximately 150% of the original tissue thickness. In such a black-and-white or grayscale representation of a health map, darker areas can represent both increases and decreases in tissue thickness, while lighter areas can represent smaller changes (increases or decreases) relative to the original measurement. FIG. 11A shows an area 1100 with tissue inflammation, as indicated by the darker areas of the health map, FIG. 11B shows an area 1102 with tissue thickness approximately the same as the original tissue, and FIG. 11E shows an area 1104 with tissue loss compared to the original thickness. As used herein, the "original" thickness or volume of corneal tissue is the thickness or volume of corneal tissue measured before the corneal implant is implanted, thereby facilitating accurate comparison of pre- and post-implant health for the corneal tissue.

[0107] FIG. 11G is a graph displaying the average corneal volume as a percentage based on the initial pre-operative corneal volume derived from the data shown in association with FIGS. 11A-11F, and further shows the total corneal tissue volume 1106 measured at different increments over a six-month period. The total tissue volume can be calculated using any suitable method. For example, the total tissue volume can be calculated by combining a sufficient number of corneal thickness measurements with the ocular surface area to which those thickness measurements are associated to obtain the corneal tissue volume. In another example, the average corneal thickness can be determined from data generated from the corneal health map illustrated in FIGS. 11A-11F, and the corneal surface area associated with the health map can then be used to calculate the average corneal volume value. In yet another example, the total tissue volume can be calculated by measuring the tissue volume of smaller areas of the cornea and then adding all of the measured volumes to cover the entire area of ​​the cornea. In FIG. 11A, the θ-degree increments are used to calculate the area of ​​the health map covered by the θ-degree arc, which is then multiplied by the average thickness measured within the region defined by the arc to generate the volume within the θ-degree arc. The arc is then rotated clockwise (or counterclockwise, as appropriate) until a "sweep" of the entire 360-degree range is completed. The total tissue volume determined using this method or other methods described above can then be compared to the total tissue volume before the implant procedure to determine the percentage change in total tissue volume, which is plotted on a graph for each time increment, as shown in FIG. 11G. The value of θ can be any suitable value, including, but not limited to, one of divisors of 360 (1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 15, 18, 20, 24, 30, 36, 40, 45, 60, 72, 90, 120, 180, 360 degrees, etc.). As an alternative to a power-based system, the location of the pachymetry or the location of the features observed in the display data can be based on a common clock face, with the top or 0 degree position of the clock referred to as the 12 o'clock position and the remaining positions based on well-known positions on the clock face.Similarly, the location of the pachymetry or the location of the features observed in the display data can be based on well-known compass directions, with north coinciding with the aforementioned 0 degree or 12 o'clock direction.

[0108] In FIG. 11E, tissue loss is primarily observed at the 9 o'clock position of the ring (as indicated by the red region 1104), while in FIG. 11F, the red region extends to the 10 o'clock position, which may indicate localized corneal tissue deterioration. However, as shown in FIG. 11G, the total corneal tissue volume increases from the 5-month measurement (FIG. 11E) to the 6-month measurement (FIG. 11F), which may indicate that the condition of the corneal tissue is improving from the 5-month measurement to the 6-month measurement, indicating that the corneal tissue inflammation is stabilizing and that the amount of tissue loss observed is small, localized, and clinically acceptable. Therefore, a physician or doctor may be interested not only in whether there is tissue loss in the cornea, but also in the location of the tissue loss, the area of ​​the eye affected, and how the tissue loss affects the health of the cornea as a whole. For this reason, it may be beneficial to consider not only local tissue thickness measurements but also the rate of change in total tissue volume when making a decision regarding the overall success or failure of an implant procedure or when determining that additional treatment is necessary.

[0109] Similarly, Figures 12A-12F show health maps generated for different subjects, respectively, one month through six months after implantation. As used herein, "subject" can refer to any suitable patient, such as a human or animal (e.g., a mammal), undergoing corneal implant therapy or other similar corneal procedures. In these figures, no red areas 1104 are observed, thus indicating a low risk and presence of corneal tissue loss after implantation. The total corneal tissue volume 1200 measured over six months in Figure 12G shows a gradual decrease in total tissue volume over the six-month monitoring period, with tissue volume consistently exceeding 100% during this period, indicating that the corneal tissue is trending toward stability and that the corneal implant procedure appears to be successful.

[0110] Similarly, Figures 13A-13F show health maps generated for yet another different subject, respectively, one to six months after implantation. Although there is a slightly red area 1104 in Figure 13F, the overall total corneal tissue volume, as shown in Figure 13G, has not decreased below its original volume, indicating that the corneal tissue is also tending to stabilize for this subject.

[0111] Figure 14 compares the changes in total corneal tissue volume 1106, 1200, and 1300 from Figures 11G, 12G, and 13G, plotted on the same graph, to illustrate the differences in the changes in total corneal tissue volume over the same time period for three different subjects treated with the same type of corneal implant. In some instances, such comparisons may be performed on multiple subjects to determine the overall effectiveness of the same corneal implant across multiple patients, to evaluate the success of the implant procedure across multiple patients, or to evaluate the performance of comparable corneal implants that differ in some respects. Any suitable statistical analysis method known in the art, such as statistical mean change (or variation) in corneal tissue volume over time and standard deviation of the analyzed sample data, can be applied to determine patterns or trends that can be inferred based on the collected data regarding corneal tissue volume. Based on the determined patterns or trends, a doctor or physician can make decisions regarding the safety and effectiveness of the corneal implant being used.

[0112] In some instances, the health map may be generated at a consistent pace, even after an initial period following implantation. For example, the health map may be generated at predetermined time increments to continuously monitor the health of a subject's cornea during the healing period, as part of a continuous examination protocol to monitor annual eye health as a component of a routine checkup, or as a technique to monitor corneal health to identify patients in need of corrective treatment. FIG. 15 shows an exemplary method 1500 used by system 100 to analyze the health map to alert a user in this regard. At step 1502, a health map of a region of the subject's cornea is generated using any suitable method as disclosed herein. Using the generated health map, the total volume of corneal tissue is calculated at step 1504, and the resulting total tissue volume of the region over a period of time is calculated and stored (e.g., in a memory device), thereby generating a continuous record of tissue volume data to be saved for analysis.

[0113] In step 1506, a loss of total tissue volume over a period of time is detected, such as by calculating the rate of change of the total tissue volume after the implant procedure compared to the original pre-implant tissue volume. In some examples, an average tissue volume can be used instead of the total tissue volume, in which case the average tissue volume can be calculated by dividing the total volume by the total area of ​​the region or health map. In step 1508, a notification is generated to alert the user to tissue loss in the cornea, as appropriate. In some examples, the notification is generated in response to calculating a rate of change between a first tissue volume in a measured region of the cornea and a second tissue volume in that region, where the first tissue volume is associated with the period before the corneal implant procedure and the second tissue volume is associated with the period after the corneal implant procedure. When the rate of change is determined to be below a predetermined threshold, a notification can be displayed indicating that the region of the cornea is experiencing tissue loss after the corneal implant procedure. In some examples, the notification can be generated in response to detecting tissue loss in the cornea after the prosthetic corneal implant procedure without calculating such a rate of change.

[0114] FIG. 16 is a cross-sectional image of the cornea of ​​an eye, which may be obtained using any suitable method, such as optical clearance tomography. The image illustrates sublayers that may monitor the health of the cornea. By way of example, the cornea may be separated into different sublayers, each sublayer defining a portion of the total thickness of the cornea at a given location. For example, an outer sublayer 1601 (or outermost sublayer) may be defined as the sublayer that includes the outer surface 1600 of the cornea, which is the region of the cornea that is in direct contact with the outside air and the eyelid. An inner sublayer 1605 (or innermost sublayer) may be defined as the sublayer that includes the inner surface 1606 of the cornea, which is the region of the cornea closest to the iris of the eye (as shown in FIG. 3). An intermediate sublayer 1603 may be defined as the sublayer located between the outer sublayer 1601 and the inner sublayer 1605. In some examples, there may be multiple intermediate sublayers 1603 that may be monitored. In some instances, one or more sublayers can be monitored to determine the health of the cornea, and in some instances, the monitored sublayers can exclude certain sublayers, such that any one (or more) of the outer, inner, and middle sublayers can be simultaneously and independently monitored.

[0115] In some instances, the sublayers are formed as a result of a procedure or surgery performed on the cornea. For example, an incision made in the corneal tissue (such as incision mark 410 in FIG. 4B ) can define the boundary between two separate sublayers, and this incision can be monitored after the procedure to allow the physician and doctor to ensure that the cornea is healing properly. For example, boundary line 1602 separating sublayers 1601 and 1603 and boundary line 1604 separating sublayers 1603 and 1605 can be formed as a result of an incision made in the corneal tissue. If the health of the sublayers on either side of the incision indicates tissue loss (e.g., if the thickness of the sublayers on either side of the incision decreases over time), this can be an indication of a potential problem with the corneal tissue.

[0116] In view of the above, in some situations it is important to consider the health of each sublayer separately and independently from the other sublayers, thereby enabling early detection and flagging of changes in health (which in some examples may be changes in thickness, volume, opacity, or any combination thereof). In some examples, middle sublayer 1603 may be an implant, such as corneal implant 400 of FIG. 4A, in which case only outer sublayer 1601 and inner sublayer 1605 are monitored, thus ignoring the implant from the health measurement. In such examples, boundary lines 1602 and 1604 define two opposing surfaces of the corneal implant.

[0117] FIG. 17 illustrates an exemplary method 1700 used by system 100 to analyze corneal tissue health at the sublayer level, as described above with respect to FIG. 16 , according to some embodiments. For example, in step 1702, a health index (e.g., thickness, volume, opacity, or any suitable combination thereof) is determined for multiple sublayers within the cornea at a first time t1, and in step 1704, a health index is determined for the sublayers at a second time t2. In step 1706, a change in the health index (e.g., indicative of corneal tissue deterioration) is detected between t1 and t2, or from t1 to t2. The change can be detected using any suitable method, including, but not limited to, performing a visual analysis of cross-sectional tomographic images obtained from the corneal tissue or comparing the beam reflectivity and signal intensity coherence of a light beam as it passes through the corneal tissue. After a change is detected, in step 1708, a notification is generated, as appropriate, alerting the user to tissue loss (or potential tissue loss) within the cornea.

[0118] Such sublayer-based analysis can be advantageous, for example, when one sublayer decreases in thickness or volume while another sublayer increases in thickness or volume, while the overall thickness or volume remains relatively the same. Thus, even if the overall thickness or volume remains relatively constant, it is possible to detect tissue loss in the sublayers if each sublayer is monitored and analyzed individually, independent of one another.

[0119] If tissue loss is detected or determined during generation of the health map, or if the rate of change in the total corneal tissue volume exceeds a certain threshold (e.g., less than about 97%, 95%, 92%, 90%, 85%, 80%, or any other suitable value therebetween, compared to the original tissue volume defining a 100% baseline), the computing device (e.g., processor) can generate an alert or notification to a user, who can be either the subject or a physician / physician responsible for monitoring the subject's corneal health. If a notification is sent to the user, the notification may include a message to seek immediate medical attention. If a notification is sent to a physician or physician, the notification may include a detailed description of when and where tissue loss in the subject's cornea may have been detected to facilitate the diagnostic process.

[0120] As can be seen, physicians find this data useful in diagnosing and monitoring the health and disease state of the eye. In one example, physicians using these technologies can monitor the health of corneal tissue monthly while a patient is undergoing healing or medical therapy. If a sudden decrease in thickness is observed, the physician can further examine the affected area of ​​the patient's eye and prescribe immediate treatment to help the patient and the eye's tissue recover. In another example, during the acute phase after implantation, observed changes in tissue volume over time can indicate the state of wound healing during the post-implant period. Edema tissue volume can be observed to shrink and then return to normal volume with expected wound healing, eventually reaching pre-implant volume. During the chronic device lifespan, regular monitoring of tissue volume and changes in tissue volume over time can identify early tissue loss that may lead to implant loss or failure without the need for a second interventional procedure, which is typically performed to stabilize tissue loss.

[0121] The aforementioned examples and implementations can be applied to detect additional or alternative conditions, such as corneal ectasia, a vision-threatening condition that can cause abnormal thinning of the cornea and permanent damage to the eye. Potential causes of corneal ectasia include keratoconus, pellucid marginal degeneration, keratoglobus, and laser eye surgery (including, but not limited to, LASIK surgery). Ectasia occurs in corneas that are already at risk or that are at risk because they are naturally thinner than average. The average corneal thickness is approximately 540 microns centrally. Ectasia occurs when the LASIK flap removes too much corneal tissue, weakening and thinning the remaining corneal tissue. Physicians typically pre-screen LASIK candidates to identify patients at risk for corneal ectasia. This process involves topography and pachymetry with OCT imaging combined with the patient's medical history to determine the potential risk for corneal ectasia. Physicians identify corneal abnormalities, paying particular attention to the thinnest points in the cornea as areas at risk for ectasia. Post-LASIK screening can also utilize OCT images to monitor corneal volume in thinned areas and signs of ectasia. Similar to keratoconus, pre- and post-LASIK monitoring is complicated by the challenges of manually correlating corneal topography with tissue volume calculations and the manual analysis required by physicians to track these calculations over time. Therefore, automated health map generation as disclosed herein offers the advantage of more accurate and thorough tissue thickness or volume calculations, the results of which can be provided on a topographical map to visually display areas most at risk for corneal ectasia for the physician's examination.

[0122] Those skilled in the art will readily appreciate that the various aspects of the present disclosure may be implemented by any number of methods and apparatus configured to perform the intended functions. It should also be noted that the accompanying drawings referred to herein are not necessarily drawn to scale and may be exaggerated to illustrate various aspects of the present disclosure, and in that regard, the drawings should not be construed as limiting.

[0123] The devices, methods, and systems shown in the figures disclosed herein are provided as examples of various features of the devices, methods, and systems, and while combinations of these illustrated features are clearly within the scope of the present invention, these examples and their features are not intended to suggest that the inventive concepts provided herein are limited to fewer features, additional features, or alternative features for one or more of those features shown in the figures. For example, it should be understood that in various embodiments, the method shown in Figure 8 can include other steps described with reference to Figures 9 or 10, as well as additional or alternative processes described with reference to other figures, and vice versa.

[0124] Various modifications and additions can be made to the exemplary embodiments described without departing from the scope of the present disclosure. For example, while the above-described embodiments refer to particular features, the scope of the present disclosure also includes embodiments having different combinations of features and embodiments that do not include all of the described features. Accordingly, the scope of the present disclosure is intended to encompass all alternatives, modifications, and variations that fall within the scope of the claims, together with all equivalents thereof. (Aspect) (Aspect 1) 1. A method for monitoring corneal tissue health, the method comprising: measuring a first health indicator of a region of corneal tissue during a first period of time; measuring a second health indicator of the region during a second period of time after the first period of time; and generating a health map of the region based on the first health status indicator and the second health status indicator; Including, the first health indicator is a first tissue thickness of the region; the second health indicator is a second tissue thickness of the region; The health map shows a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period. (Aspect 2) 1. A method for monitoring corneal tissue health, the method comprising: measuring a first health indicator of a region of corneal tissue during a first period of time; measuring a second health indicator of the region during a second period of time after the first period of time; and generating a health map of the region based on the first health status indicator and the second health status indicator; Including, the first health indicator is a first tissue volume of the region; the second health indicator is a second tissue volume of the region; The health map shows a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period. (Aspect 3) The method of aspect 1 or 2, wherein the first health indicator and the second health indicator are measured by obtaining cross-sectional images of the region of corneal tissue at the first time period and the second time period. (Aspect 4) cross-sectional images of the region of corneal tissue at the first time period and the second time period; (a) a first set of cross-sectional images of the region taken during the first time period; and (b) a second set of cross-sectional images of the region taken during the second time period; 4. The method of aspect 3, further comprising comparing the first set of cross-sectional images to the second set of cross-sectional images to generate the health map. (Aspect 5) The method of any one of aspects 1 to 4, wherein the area includes at least one sublayer of the corneal tissue being monitored, and the first health indicator and the second health indicator are associated with the at least one sublayer. (Aspect 6) 6. The method of embodiment 5, wherein the at least one sublayer comprises one or more of an outer sublayer, an inner sublayer, or an intermediate sublayer disposed between the outer sublayer and the inner sublayer. (Aspect 7) The method of any one of aspects 1 to 6, further comprising calculating a rate of change between the first health indicator and the second health indicator from the first period to the second period based on the health map of the region of the cornea. (Aspect 8) 8. The method of embodiment 7, further comprising determining a predicted health indicator for the region during a third period of time after the second period of time based on the second health indicator for the region and the rate of change. (Aspect 9) measuring one or more intermediate health indicators of the region at one or more time points between the first time period and the second time period; The method according to any one of aspects 1 to 8, wherein the health map shows continuous changes between the intermediate health status indicators. (Aspect 10) 10. The method of embodiment 9, further comprising outputting the continuous changes among the first health status index, the second health status index, and the intermediate health status index as a graph over time. (Aspect 11) identifying, on the health map, at least one sub-region within the region of the cornea that exhibits a change in the first health indicator and the second health indicator that exceeds a threshold range; and 11. The method of any one of aspects 1-10, further comprising displaying, on a user interface, the at least one sub-region overlaid on the health map. (Aspect 12) determining a diagnosis of the region of corneal tissue based on the health map and a change between the first health indicator and the second health indicator; and displaying the diagnosis and the health map on a user interface; further comprising 11. The method of any one of aspects 1 to 10, wherein the diagnosis is selectable from a list of corneal diseases stored in a memory unit. (Aspect 13) displaying the health map of the region as a user interactive map on a user interface; further comprising Aspect 11. The method of any one of aspects 1-10, wherein the user interface is configured to receive user input and display additional information corresponding to the received user input. (Aspect 14) 14. The method of any one of aspects 1 to 13, wherein the health map is a topographical map of the region. (Aspect 15) The method of any one of embodiments 1 to 14, wherein the health indicator is measured by optical coherence tomography (OCT). (Aspect 16) calculating a percent change between the first health status indicator of the region and the second health status indicator of the region; determining that the percent change is below a predetermined threshold; and displaying a notification on a user interface that the area of ​​the cornea is experiencing tissue loss following a corneal implant procedure; further comprising The method of any one of aspects 1 to 2, wherein the first health indicator is associated with a first period of time before the corneal implant is implanted, and the second health indicator is associated with a second period of time after the corneal implant is implanted. (Aspect 17) a corneal measurement device configured to measure a first health indicator of a region of corneal tissue during a first time period and to measure a second health indicator of the region during a second time period after the first time period; and a processing unit configured to receive the first health indicator and the second health indicator from the corneal measurement device and generate a health map of the region based on the first health indicator and the second health indicator; Including, the first health indicator is a first tissue thickness of the region, and the second health indicator is a second tissue thickness of the region; the health map showing a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period; Corneal tissue health monitoring system. (Aspect 18) a corneal measurement device configured to measure a first health indicator of a region of corneal tissue during a first time period and to measure a second health indicator of the region during a second time period after the first time period; and a processing unit configured to receive the first health indicator and the second health indicator from the corneal measurement device and generate a health map of the region based on the first health indicator and the second health indicator; Including, the first health indicator is a first tissue volume of the region, and the second health indicator is a second tissue volume of the region; the health map showing a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period; Corneal tissue health monitoring system. (Aspect 19) A corneal tissue health monitoring system as described in aspect 17 or 18, wherein the first health indicator and the second health indicator are measured by acquiring cross-sectional images of the area of ​​corneal tissue during the first period and the second period. (Aspect 20) cross-sectional images of the region of corneal tissue at the first time period and the second time period; (a) a first set of cross-sectional images of the region taken during the first time period; and (b) a second set of cross-sectional images of the region taken during the second time period; Including, 20. The corneal tissue health monitoring system of claim 19, wherein the processing unit is further configured to compare the first set of cross-sectional images with the second set of cross-sectional images to generate a health map. (Aspect 21) A corneal tissue health monitoring system as described in any one of aspects 17 to 20, wherein the area includes at least one sublayer of the corneal tissue being monitored, and the first health indicator and the second health indicator are associated with the at least one sublayer. (Aspect 22) 22. The corneal tissue health monitoring system of claim 21, wherein the at least one sublayer comprises one or more of an outer sublayer, an inner sublayer, or an intermediate sublayer disposed between the outer sublayer and the inner sublayer. (Aspect 23) A corneal tissue health monitoring system as described in any one of aspects 17 to 22, wherein the processing unit is further configured to calculate a rate of change between the first health indicator and the second health indicator from the first period to the second period based on the health map of the region. (Aspect 24) A corneal tissue health monitoring system as described in aspect 23, wherein the processing unit is further configured to determine a predicted health indicator of the region during a third period after the second period based on the second health indicator of the region and the rate of change. (Aspect 25) A corneal tissue health monitoring system as described in any one of aspects 17 to 24, wherein the corneal measurement device is further configured to measure one or more intermediate health indicators of the area between the first period and the second period, and the health map shows continuous changes between the intermediate health indicators. (Aspect 26) A corneal tissue health monitoring system as described in aspect 25, wherein the processing unit is further configured to output continuous changes between the first health index, the second health index, and the intermediate health index as a graph over time. (Aspect 27) the processing unit is further configured to identify, on the health map, at least one subregion within the region of the cornea that exhibits a change in the first health indicator and the second health indicator that exceeds a threshold range; A corneal tissue health monitoring system according to any one of aspects 17 to 26, wherein the corneal tissue health monitoring system further includes a user interface configured to display the at least one sub-region overlaid on the health map. (Aspect 28) further comprising a memory unit configured to store a list of corneal diseases; the processing unit is further configured to determine a diagnosis for the region of corneal tissue based on the health map and a change between the first health indicator and the second health indicator, the diagnosis being selectable from a list of corneal diseases stored in the memory unit; and 27. The corneal tissue health monitoring system of any one of aspects 17 to 26, wherein the corneal tissue health monitoring system further comprises a user interface configured to display diagnostic and health maps. (Aspect 29) The corneal tissue health monitoring system of embodiment 28 further includes a user interface configured to display the health map of the region as a user interactive map, receive user input, and display additional information corresponding to the received user input. (Aspect 30) A corneal tissue health monitoring system as described in aspect 29, wherein the user interface is further configured to open a new window displaying the additional information in response to detecting the user input, and the additional information is a cross-sectional image of the area selected by the user on a user interactive map. (Aspect 31) 31. The corneal tissue health monitoring system of any one of aspects 17 to 30, wherein the health map is a topographical map of the region. (Aspect 32) 32. The corneal tissue health monitoring system of any one of aspects 17 to 31, wherein the health indicator is measured by optical coherence tomography (OCT). (Aspect 33) The processing unit further includes a user interface. calculating a percent change between the first health status indicator of the region and the second health status indicator of the region; determining that the percent change is below a predetermined threshold; and displaying a notification on a user interface that the region of the cornea is experiencing tissue loss following a corneal implant procedure; Including, The corneal tissue health monitoring system of aspect 17 or 18, wherein the first health indicator is associated with a first period before the corneal implant is implanted, and the second health indicator is associated with a second period after the corneal implant is implanted.

Claims

1. 1. A method for monitoring corneal tissue health, the method comprising: measuring a first health indicator of a region of corneal tissue during a first period of time; measuring a second health indicator of the region during a second period of time after the first period of time; and generating a health map of the region based on the first health status indicator and the second health status indicator; Including, the first health indicator is a first tissue thickness of the region; the second health indicator is a second tissue thickness of the region; the health map showing a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period; and, calculating a percentage change between the first health status indicator of the region and the second health status indicator of the region; determining that the percent change is below a predetermined threshold; and displaying a notification on a user interface that the area of ​​the cornea is experiencing tissue loss following a corneal implant procedure; further comprising The method, wherein the first health indicator is associated with a first period of time before the corneal implant is implanted, and the second health indicator is associated with a second period of time after the corneal implant is implanted.

2. 1. A method for monitoring corneal tissue health, the method comprising: measuring a first health indicator of a region of corneal tissue during a first period of time; measuring a second health indicator of the region during a second period of time after the first period of time; and generating a health map of the region based on the first health status indicator and the second health status indicator; Including, the first health indicator is a first tissue volume of the region; the second health indicator is a second tissue volume of the region; the health map showing a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period; and, calculating a percentage change between the first health status indicator of the region and the second health status indicator of the region; determining that the percent change is below a predetermined threshold; and displaying a notification on a user interface that the area of ​​the cornea is experiencing tissue loss following a corneal implant procedure; further comprising The method, wherein the first health indicator is associated with a first period of time before the corneal implant is implanted, and the second health indicator is associated with a second period of time after the corneal implant is implanted.

3. 3. The method of claim 1, wherein the first health indicator and the second health indicator are measured by obtaining cross-sectional images of the region of corneal tissue at the first time period and the second time period.

4. cross-sectional images of the region of corneal tissue at the first time period and the second time period; (a) a first set of cross-sectional images of the region taken during the first time period; and (b) a second set of cross-sectional images of the region taken during the second time period; 4. The method of claim 3, further comprising comparing the first set of cross-sectional images with the second set of cross-sectional images to generate the health map.

5. The method of any one of claims 1 to 2, wherein the region includes at least one sublayer of the corneal tissue being monitored, and the first health indicator and the second health indicator are associated with the at least one sublayer.

6. The method of claim 5 , wherein the at least one sublayer comprises one or more of an outer sublayer, an inner sublayer, or an intermediate sublayer disposed between the outer sublayer and the inner sublayer.

7. The method of any one of claims 1 to 2, further comprising calculating a rate of change between the first health indicator and the second health indicator from the first time period to the second time period based on the health map of the region of the cornea.

8. 8. The method of claim 7, further comprising determining a predicted health indicator for the region during a third period after the second period based on the second health indicator for the region and the rate of change.

9. measuring one or more intermediate health indicators of the region at one or more time points between the first time period and the second time period; the health map showing continuous changes between the intermediate health status indicators; or measuring one or more intermediate health indicators of the region at one or more time points between the first time period and the second time period; the health map showing continuous changes between the intermediate health status indicators; and The method of any one of claims 1 to 2, further comprising outputting continuous changes between the first health status index, the second health status index and the intermediate health status index as a graph over time.

10. identifying, on the health map, at least one sub-region within the region of the cornea that exhibits a change in the first health indicator and the second health indicator that exceeds a threshold range; and The method of any one of claims 1 to 2, further comprising displaying, on a user interface, the at least one sub-region overlaid on the health map.

11. The processing unit: determining a diagnosis of the region of corneal tissue based on the health map and a change between the first health indicator and the second health indicator; and displaying the diagnosis and the health map on a user interface; further comprising The method of any one of claims 1 to 2, wherein the diagnosis is selectable from a list of corneal disorders stored in a memory unit.

12. displaying the health map of the region as a user interactive map on a user interface; The method of any one of claims 1 to 2, wherein the user interface is configured to receive user input and display additional information corresponding to the received user input.

13. the health map is a topographical map of the region; or The method according to any one of claims 1 to 2, wherein the health indicator is measured by optical coherence tomography (OCT).

14. a corneal measurement device configured to measure a first health indicator of a region of corneal tissue during a first time period and to measure a second health indicator of the region during a second time period after the first time period; and a processing unit configured to receive the first health indicator and the second health indicator from the corneal measurement device and generate a health map of the region based on the first health indicator and the second health indicator; Including, the first health indicator is a first tissue thickness of the region, and the second health indicator is a second tissue thickness of the region; the health map indicating a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period; and, The processing unit further includes a user interface. calculating a percentage change between the first health status indicator of the region and the second health status indicator of the region; determining that the percent change is below a predetermined threshold; and displaying a notification on a user interface that the region of the cornea is experiencing tissue loss following a corneal implant procedure; It is configured to A corneal tissue health monitoring system, wherein the first health indicator is associated with a first period before the corneal implant is implanted, and the second health indicator is associated with a second period after the corneal implant is implanted.

15. a corneal measurement device configured to measure a first health indicator of a region of corneal tissue during a first time period and to measure a second health indicator of the region during a second time period after the first time period; and a processing unit configured to receive the first health indicator and the second health indicator from the corneal measurement device and generate a health map of the region based on the first health indicator and the second health indicator; Including, the first health indicator is a first tissue volume of the region, and the second health indicator is a second tissue volume of the region; the health map indicating a change between the first health indicator and the second health indicator measured in the region of the cornea from the first time period to the second time period; and, The processing unit further includes a user interface. calculating a percentage change between the first health status indicator of the region and the second health status indicator of the region; determining that the percent change is below a predetermined threshold; and displaying a notification on a user interface that the region of the cornea is experiencing tissue loss following a corneal implant procedure; It is configured to A corneal tissue health monitoring system, wherein the first health indicator is associated with a first period before the corneal implant is implanted, and the second health indicator is associated with a second period after the corneal implant is implanted.

16. 16. The corneal tissue health monitoring system of claim 14 or 15, wherein the first health indicator and the second health indicator are measured by acquiring cross-sectional images of the area of ​​corneal tissue during the first period and the second period.

17. cross-sectional images of the region of corneal tissue at the first time period and the second time period; (a) a first set of cross-sectional images of the region taken during the first time period; and (b) a second set of cross-sectional images of the region taken during the second time period; Including, 17. The corneal tissue health monitoring system of claim 16, wherein the processing unit is further configured to compare the first set of cross-sectional images with the second set of cross-sectional images to generate a health map.

18. 16. A corneal tissue health monitoring system as described in any one of claims 14 to 15, wherein the area includes at least one sublayer of the corneal tissue being monitored, and the first health indicator and the second health indicator are associated with the at least one sublayer.

19. 20. The corneal tissue health monitoring system of claim 18, wherein the at least one sublayer comprises one or more of an outer sublayer, an inner sublayer, or an intermediate sublayer disposed between the outer sublayer and the inner sublayer.

20. 16. A corneal tissue health monitoring system according to any one of claims 14 to 15, wherein the processing unit is further configured to calculate a rate of change between the first health indicator and the second health indicator from the first period to the second period based on the health map of the region.

21. 21. The corneal tissue health monitoring system of claim 20, wherein the processing unit is further configured to determine a predicted health indicator of the region during a third period after the second period based on the second health indicator of the region and a rate of change.

22. 16. A corneal tissue health monitoring system as described in any one of claims 14 to 15, wherein the corneal measurement device is further configured to measure one or more intermediate health indicators of the region between the first period and the second period, and the health map shows continuous changes between the intermediate health indicators.

23. 23. The corneal tissue health monitoring system of claim 22, wherein the processing unit is further configured to output continuous changes between the first health index, the second health index, and the intermediate health index as a graph over time.

24. the processing unit is further configured to identify, on the health map, at least one subregion within the region of the cornea that exhibits a change in the first health indicator and the second health indicator that exceeds a threshold range; The corneal tissue health monitoring system of any one of claims 14 to 15, further comprising a user interface configured to display the at least one sub-region overlaid on the health map.

25. further comprising a memory unit configured to store a list of corneal diseases; the processing unit is further configured to determine a diagnosis for the region of corneal tissue based on the health map and a change between the first health indicator and the second health indicator, the diagnosis being selectable from a list of corneal diseases stored in the memory unit; and The corneal tissue health monitoring system of any one of claims 14 to 15, further comprising a user interface configured to display diagnostic and health maps.

26. 26. The corneal tissue health monitoring system of claim 25, further comprising a user interface configured to display the regional health map as a user interactive map, receive user input, and display additional information corresponding to the received user input.

27. 27. The corneal tissue health monitoring system of claim 26, wherein the user interface is further configured to open a new window displaying the additional information in response to detecting the user input, the additional information being a cross-sectional image of the area selected by the user on a user interactive map.

28. The corneal tissue health monitoring system of any one of claims 14 to 15, wherein the health map is a topographical map of the region.

29. The corneal tissue health monitoring system of any one of claims 14 to 15, wherein the health indicator is measured by optical coherence tomography (OCT).

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