{"doi":"10.1167/tvst.9.2.56","title":"Artificial Intelligence for Automated Overlay of Fundus Camera and Scanning Laser Ophthalmoscope Images","abstract":"Purpose: The purpose of this study was to evaluate the ability to align two types of retinal images taken on different platforms; color fundus (CF) photographs and infrared scanning laser ophthalmoscope (IR SLO) images using mathematical warping and artificial intelligence (AI). Methods: We collected 109 matched pairs of CF and IR SLO images. An AI algorithm utilizing two separate networks was developed. A style transfer network (STN) was used to segment vessel structures. A registration network was used to align the segmented images to each. Neither network used a ground truth dataset. A conventional image warping algorithm was used as a control. Software displayed image pairs as a 5 × 5 checkerboard grid composed of alternating subimages. This technique permitted vessel alignment determination by human observers and 5 masked graders evaluated alignment by the AI and conventional warping in 25 fields for each image. Results: < 0.0001). The average number of good/excellent matches increased from 90.5% to 94.4% with AI method. Conclusions: AI permitted a more accurate overlay of CF and IR SLO images than conventional mathematical warping. This is a first step toward developing an AI that could allow overlay of all types of fundus images by utilizing vascular landmarks. Translational Relevance: The ability to align and overlay imaging data from multiple instruments and manufacturers will permit better analysis of this complex data helping understand disease and predict treatment.","journal":"Translational Vision Science & Technology","year":2020,"id":73038,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9407,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":374355,"name":"Cheolhong An","orcid":"0000-0003-2821-7386","position":1,"is_corresponding":false},{"id":384829,"name":"Dirk‐Uwe Bartsch","orcid":"0000-0003-0955-8708","position":2,"is_corresponding":false},{"id":384830,"name":"Mahima Jhingan","orcid":"0000-0002-9969-3411","position":3,"is_corresponding":false},{"id":384831,"name":"Manuel J. Amador-Patarroyo","orcid":"0000-0001-6058-5678","position":4,"is_corresponding":false},{"id":339517,"name":"Christopher P. Long","orcid":"0000-0001-7803-2596","position":5,"is_corresponding":false},{"id":384832,"name":"Junkang Zhang","orcid":"0000-0003-2121-1467","position":6,"is_corresponding":false},{"id":386301,"name":"Yiqian Wang","orcid":null,"position":7,"is_corresponding":false},{"id":384833,"name":"Alison Chan","orcid":"0000-0002-2651-4873","position":8,"is_corresponding":false},{"id":384834,"name":"Samantha Madala","orcid":"0000-0003-0677-9716","position":9,"is_corresponding":false},{"id":384835,"name":"Truong Q. Nguyen","orcid":"0000-0002-5022-063X","position":10,"is_corresponding":false},{"id":342572,"name":"William R. Freeman","orcid":"0000-0001-9979-2500","position":11,"is_corresponding":false},{"id":384828,"name":"Melina Cavichini","orcid":"0000-0003-0444-113X","position":0,"is_corresponding":true}],"reference_count":45,"raw_metadata":null,"created_at":"2026-07-18T21:45:32.034078Z","pmid":"33173612","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}