It takes rigorous quality-by-design R&D process, state-of-the-art cross functional expertise, capabilities and partnerships to develop the AI-solutions that RetInSight envisions bringing to eye care professionals, patients and payors in the coming years. Please find our scientific publications here.

  • Fundus autofluorescence and optical coherence tomography
    The Royal Collage of Ophthalmologists, 2021
    Schmidt-Erfurth U, Bui P, Reiter G, Fabianska M, Waldstein S, Grechenig C, Bogunovic H, Arikan M.
  • Linking Function and Structure with ReSenseNet: Predicting Retinal Sensitivity from Optical Coherence Tomography using Deep Learning.
    Ophthalmol Retina. 2022 Feb 5:S2468-6530(22)00043-4
    Seeböck P, Vogl WD, Waldstein SM, Orlando JI, Baratsits M, Alten T, Arikan M, Mylonas G, Bogunović H, Schmidt-Erfurth U.
  • Comparison of early diabetic retinopathy staging in asymptomatic patients between autonomous AI-based screening and human-graded ultra-widefield colour fundus images.
    Eye (Lond). 2022 Feb 7
    Sedova A, Hajdu D, Datlinger F, Steiner I, Neschi M, Aschauer J, Gerendas BS, Schmidt-Erfurth U, Pollreisz A.
  • Baseline predictors for subretinal fibrosis in neovascular age-related macular degeneration.
    Sci Rep. 2022 Jan 7;12(1):88
    Roberts PK, Schranz M, Motschi A, Desissaire S, Hacker V, Pircher M, Sacu S, Buehl W, Hitzenberger CK, Schmidt-Erfurth UM.
  • A systematic correlation of central subfield thickness (CSFT) with retinal fluid volumes quantified by deep learning in the major exudative macular diseases.
    Retina. 2021 Dec 17
    Pawloff M, Bogunovic H, Gruber A, Michl M, Riedl S, Schmidt-Erfurth U.
  • Validation of an automated fluid algorithm on real-world data of neovascular age-related macular degeneration over five years
    Retina: September 2022 – Volume 42 – Issue 9 – p 1673-1682
    Gerendas BS, Sadeghipour A, Michl M, Goldbach F, Mylonas G, Gruber A, Alten T, Leingang O, Sacu S, Bogunovic H, Schmidt-Erfurth U
  • Leveraging artificial intelligence in clinical management of nAMD
    Conference | EURETINA September 12, 2022
    Caroline Richards
  • AI-based monitoring of retinal fluid in disease activity and under therapy.
    Prog Retin Eye Res. 2021; Article in press
    Schmidt-Erfurth U, Reiter Gregor, Riedl S, Seeböck P, Vogl WD, Blodi B, Domalpally A, Fawzi A, Jia Y, Sarraf D, Bogunović H.
  • Artificial intelligence in retina.
    [Prog Retin Eye Res. 2018; 67:1-29]
    Schmidt-Erfurth U, Sadeghipour A, Gerendas BS, Waldstein SM, Bogunović H.
  • A paradigm shift in imaging biomarkers in neovascular age-related macular degeneration.
    [Prog Retin Eye Res. 2016; 50: 1-24]
    Schmidt-Erfurth U, Waldstein SM.
  • Fully Automated Detection and Quantification of Macular Fluid in OCT Using Deep Learning
    [Ophthalmology. 2018;125(4):549-558]
    Schlegl T, Waldstein SM, Bogunovic H, Endstrasser F, Sadeghipour A, Philip AM, Podkowinski D, Gerendas BS, Langs G, Schmidt-Erfurth U
  • Application of Automated Quantification of Fluid Volumes to Anti-VEGF Therapy of Neovascular Age-Related Macular Degeneration.
    [Ophthalmology. 2020; 127(9):1211-1219]
    Schmidt-Erfurth U, Vogl WD, Jampol LM, Bogunović H.
  • Analysis of Fluid Volume and its Impact on Visual Acuity in the FLUID Study as Quantified with Deep Learning.
    [Retina. 2020 Nov 18. Online ahead of print]
    Reiter GS, Grechenig C, Vogl WD, Guymer RH, Arnold JJ, Bogunovic H, Schmidt-Erfurth U.
  • RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge.
    [IEEE Trans Med Imaging. 2019;38(8):1858-1874]
    Bogunovic H, Venhuizen F, Klimscha S, Apostolopoulos S, Bab-Hadiashar A, Bagci U, Beg MF, Bekalo L, Chen Q, Ciller C, Gopinath K, Gostar AK, Jeon K, Ji Z, Kang SH, Koozekanani DD, Lu D, Morley D, Parhi KK, Park HS, Rashno A, Sarunic M, Shaikh S, Sivaswamy J, Tennakoon R, Yadav S, De Zanet S, Waldstein SM, Gerendas BS, Klaver C, Sanchez CI, Schmidt-Erfurth U.
  • Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration.
    [Ophthalmol Retina. 2018, 2(1):24-30]
    Schmidt-Erfurth U, Bogunovic H, Sadeghipour A, Schlegl T, Langs G, Gerendas BS, Osborne A, Waldstein SM.
  • Prediction of Individual Disease Conversion in Early AMD Using Artificial Intelligence.
    [Invest Ophthalmol Vis Sci. 2018;59(8):3199-3208]
    Schmidt-Erfurth U, Waldstein SM, Klimscha S, Sadeghipour A, Hu X, Gerendas BS, Osborne A, Bogunovic H.
  • Characterization of Drusen and Hyperreflective Foci as Biomarkers for Disease Progression in Age-Related Macular Degeneration Using Artificial Intelligence in Optical Coherence Tomography
    [JAMA Ophthalmol. 2020;138(7):740-747]
    Waldstein SM, Vogl WD, Bogunovic H, Sadeghipour A, Riedl S, Schmidt-Erfurth U.
  • Role of Deep Learning-Quantified Hyperreflective Foci for the Prediction of Geographic Atrophy Progression.
    [Am J Ophthalmol. 2020;216: 257-270]
    Schmidt-Erfurth U, Bogunovic H, Grechenig C, Bui P, Fabianska M, Waldstein S, Reiter GS.
  • Subretinal Drusenoid Deposits and Photoreceptor Loss Detecting Global and Local Progression of Geographic Atrophy by SD-OCT Imaging.
    [Invest Ophthalmol Vis Sci. 2020;61(6):11]
    Reiter GS, Told R, Schranz M, Baumann L, Mylonas G, Sacu S, Pollreisz A, Schmidt-Erfurth U.
  • Quantification of Fluid Resolution and Visual Acuity Gain in Patients With Diabetic Macular Edema Using Deep Learning: A Post Hoc Analysis of a Randomized Clinical Trial.
    [JAMA Ophthalmol. 2020; 138(9):945-953]
    Roberts PK, Vogl WD, Gerendas BS, Glassman AR, Bogunovic H, Jampol LM, Schmidt-Erfurth UM.
  • Computational image analysis for prognosis determination in DME.
    [Vision Res. 2017; 139: 204-210]
    Gerendas BS, Bogunovic H, Sadeghipour A, Schlegl T, Langs G, Waldstein SM, Schmidt-Erfurth U.
  • Topographic Analysis of Photoreceptor Loss Correlated with Disease Morphology in Neovascular Age-Related Macular Degeneration.
    [Retina. 2020;40(11):2148-2157]
    Riedl S, Cooney L, Grechenig C, Sadeghipour A, Pablik E, Seaman JW 3rd, Waldstein SM, Schmidt-Erfurth U.
  • Automated Quantification of Photoreceptor alteration in macular disease using Optical Coherence Tomography and Deep Learning.
    [Sci Rep. 2020; 10(1): 5619]
    Orlando JI, Gerendas BS, Riedl S, Grechenig C, Breger A, Ehler M, Waldstein SM, Bogunović H, Schmidt-Erfurth U.
  • f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks.
    [Med Image Anal. 2019;54:30-44]
    Schlegl T, Seeböck P, Waldstein SM, Langs G, Schmidt-Erfurth U.
  • Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT.
    [IEEE Trans Med Imaging. 2020;39(1):87-98. Erratum in: IEEE Trans Med Imaging. 2020;39(4):1291]
    Seebock P, Orlando JI, Schlegl T, Waldstein SM, Bogunovic H, Klimscha S, Langs G, Schmidt-Erfurth U.
  • Unbiased identification of novel subclinical imaging biomarkers using unsupervised deep learning.
    [Sci Rep. 2020; 10(1):12954]
    Waldstein SM, Seeböck P, Donner R, Sadeghipour A, Bogunović H, Osborne A, Schmidt-Erfurth U.


  • Guidelines for the Management of Retinal Vein Occlusion by the European Society of Retina Specialists (EURETINA).
    [Ophthalmologica. 2019;242(3):123-162]
    Schmidt-Erfurth U, Garcia-Arumi J, Gerendas BS, Midena E, Sivaprasad S, Tadayoni R, Wolf S, Loewenstein A.
  • Guidelines for the Management of Diabetic Macular Edema by the European Society of Retina Specialists (EURETINA).
    [Ophthalmologica. 2017;237(4):185-2229]
    Schmidt-Erfurth U, Garcia-Arumi J, Bandello F, Berg K, Chakravarthy U, Gerendas BS, Jonas J, Larsen M, Tadayoni R, Loewenstein A.
  • Guidelines for the management of neovascular age-related macular degeneration by the European Society of Retina Specialists (EURETINA).
    [Br J Ophthalmol. 2014;98(9):1144-67]
    Schmidt-Erfurth U, Chong V, Loewenstein A, Larsen M, Souied E, Schlingemann R, Eldem B, Monés J, Richard G, Bandello F.
  • Consensus Nomenclature for Reporting Neovascular Age-Related Macular Degeneration Data: Consensus on Neovascular Age-Related Macular Degeneration Nomenclature Study Group.
    [Ophthalmology. 2020;127(5):616-636. Erratum in: Ophthalmology. 2020;127(10):1434-1435]
    Spaide RF, Jaffe GJ, Sarraf D, Freund KB, Sadda SR, Staurenghi G, Waheed NK, Chakravarthy U, Rosenfeld PJ, Holz FG, Souied EH, Cohen SY, Querques G, Ohno-Matsui K, Boyer D, Gaudric A, Blodi B, Baumal CR, Li X, Coscas GJ, Brucker A, Singerman L, Luthert P, Schmitz-Valckenberg S, Schmidt-Erfurth U, Grossniklaus HE, Wilson DJ, Guymer R, Yannuzzi LA, Chew EY, Csaky K, Monés JM, Pauleikhoff D, Tadayoni R, Fujimoto J.
  • Deliberations of an International Panel of Experts on OCTA Nomenclature of nAMD.
    [Ophthalmology. 2020: S0161-6420(20)31198-2]
    Mendonça LSM, Perrott-Reynolds R, Schwartz R, Madi HA, Cronbach N, Gendelman I, Muldrew A, Bannon F, Balaskas K, Gemmy Cheung CM, Fawzi A, Ferrara D, Freund KB, Fujimoto J, Munk MR, Querques G, Ribeiro R, Rosenfeld PJ, Sadda SR, Sahni J, Sarraf D, Spaide RF, Schmidt-Erfurth U, Souied E, Staurenghi G, Tadayoni R, Wang RK, Chakravarthy U, Waheed NK.