# US 12,112,480 B2 · Systems and methods for processing, storage and retrieval of ocular images > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,112,480 B2 - Document ID: US12112480B2 - Status: Granted - Kind: B2 - Application number: 18/107,358 - Filed: 2023-02-08 - Published: 2023-10-05 - Granted: 2024-10-08 - Earliest claimed: 2016-10-13 - Assignees: Translatum Medicus Inc. - Applicants: Translatum Medicus, Inc. - Inventors: Shelley Romayne Boyd; Natalie Pankova - Web page: https://patentgrep.com/patent/US12112480B2 ## CPC - G06T 7/0014: {using an image reference approach} - A61B 3/024: for determining the visual field, e.g. perimeter types - A61B 3/028: for testing visual acuity; for determination of refraction, e.g. phoropters - A61B 3/102: {for optical coherence tomography [OCT]} - A61B 3/1025: {for confocal scanning} - A61B 3/12: for looking at the eye fundus, e.g. ophthalmoscopes (A61B3/13 takes precedence) - A61B 3/14: Arrangements specially adapted for eye photography - A61B 5/0013: {Medical image data (A61B1/00011, A61B6/56, A61B8/56 take precedence)} - A61B 5/398: Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG] - G16H 30/40: for processing medical images, e.g. editing - G06T 2207/10048: Infrared image - G06T 2207/10064: Fluorescence image - G06T 2207/10101: Optical tomography; Optical coherence tomography [OCT] - G06T 2207/30041: Eye; Retina; Ophthalmic - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract Disclosed herein are computer systems for, in part, image processing. Also disclosed herein are systems for processing ocular images of multiple imaging modalities to detect ocular diseases. Also disclosed herein are method comprising systems as described herein. ## Claims ### Claim 1 A method of detecting an ocular disease in a subject comprising: a. administering systemically to the subject a fluorescent agent, wherein the fluorescent agent is internalized by a cell from the subject having the ocular disease, and wherein the internalized agent produces a fluorescent emission within the cell, wherein the fluorescent emission within the cell is captured by an imaging modality, wherein the imaging modality comprises delayed near-infrared analysis (DNIRA), thereby producing an image data; b. analyzing the fluorescent emission using an algorithm; wherein the algorithm comprises: i. detecting a pattern of fluorescence from the image data from the subject; ii. comparing the pattern of fluorescence from the image data from the subject to a pattern of fluorescence from a control subject; and iii. detecting the ocular disease if the image data from the subject has a greater or lesser degree of fluorescence than the image data from the control subject, wherein the algorithm further comprises segmenting the image data based on one or more features to form a segmented image data, the method further comprises comparing the segmented image data to a second imaging modality, the second imaging modality is selected from infra-red reflectance (IR), confocal scanning laser ophthalmoscopy (cSLO), fundus autofluorescence (FAF), color fundus photography (CFP), optical coherence tomography (OCT), and OCT-angiography, the comparing the segmented image data comprises a delta analysis of the segmented image data, wherein the delta analysis comprises generating subtracted ocular images representative of changes between the image data from the control subject and the image data from the subject, and the delta analysis comprises storing the subtracted ocular images in a database. ### Claim 2 (depends on 1) The method of claim 1, wherein the cell is localized in ocular tissue of the subject. ### Claim 3 (depends on 1) The method of claim 1, wherein the cell is selected from a phagocytic cell, macrophage, retinal pigment epithelial cell, or photoreceptor. ### Claim 4 (depends on 3) The method of claim 3, wherein the cell is a macrophage, wherein the macrophage is an inflammatory macrophage, perivascular macrophage, parenchymal macrophage, microglial cell, dendritic cell, or antigen-presenting cell. ### Claim 5 (depends on 1) The method of claim 1, wherein the internalized agent produces a fluorescent emission at least 2 hours after the administering and less than 7 days after administering. ### Claim 6 (depends on 1) The method of claim 1, wherein the pattern of fluorescence comprises hyperfluorescence or hypofluorescence. ### Claim 7 (depends on 1) The method of claim 1, wherein the fluorescent agent is a near-infrared dye, and wherein the near-infrared dye is indocyanine green. ### Claim 8 (depends on 1) The method of claim 1, wherein the one or more features are selected from circularity, granularity, area, location relative to fovea, location relative to optic nerve head, location relative to periphery, number, clustering, thickness, degree of hyperfluorescence or hypofluorescence, degree of hyper-reflectance or hypo-reflectance, softness or hardness of edges, confluence between or joining of individual features, and presence or absence of known features in other modalities, or wherein one or more features comprise a hyperfluorescent dot. ### Claim 9 (depends on 1) The method of claim 1, further comprising comparing the segmented image data to a second segmented image data generated at a subsequent clinical visit or a prior clinical visit. ### Claim 10 (depends on 1) The method of claim 1, further comprising comparing the segmented image data to a patient risk factor, a second imaging modality, a functional modality, or an epigenetic factor, and wherein the patient risk factor is selected from drusen, RPE detachments, geographic atrophy, choroidal neovascularization, genetic single nucleotide polymorphisms, copy number variants, full genome sequencing, ocular biomarkers, or systemic biomarkers, or any combination thereof. ### Claim 11 (depends on 1) The method of claim 1, wherein the delta analysis comprises determining changes between the segmented image data acquired from the subject during different clinical visits. ### Claim 12 (depends on 1) The method of claim 1, wherein the delta analysis comprises determining changes between the segmented image data acquired from the subject corresponding and a plurality of different imaging modalities. ### Claim 13 (depends on 1) The method of claim 1, further comprising comparing the segmented image data to a functional modality, wherein the functional modality is selected from microperimetry, electroretinography (ERG), visual field testing, dark adaptometry (DA), and low luminance visual acuity testing. ### Claim 14 (depends on 1) The method of claim 1, wherein the algorithm further comprises a process for transforming image data for display. ### Claim 15 (depends on 14) The method of claim 14, wherein the method further comprises: a. preprocessing the image data by a registration and a normalization of the image data; b. post-processing the image data, comprising: i. transforming the image data to generate an output image data, ii. displaying changes in segments of the image data over time; and iii. generating a graphical user interface of visual elements representative of the image output data. ### Claim 16 (depends on 1) The method of claim 1, wherein the algorithm further comprises disease diagnosis, risk stratification, prognosis or a selection of a treatment. ### Claim 17 (depends on 1) The method of claim 1, where the imaging method is used as a surrogate biomarker for diagnosis, prognosis, disease progression, clinical trial design, or any combination thereof.