News & Research

Our latest updates on new discoveries, developments and technology.

Topcon Healthcare to Partner with RetInSight

RetInSight successfully passes TÜV SÜD Audit on the way to MDR certification for medical devices / medical device software

TÜV SÜD Product Service has assessed RetInSight’s Quality Management System including the product documentation according to the requirements of MDR 2017/745. Based on the results of the assessment, RetInSight is recommended for certification according to MDR 2017/745 to the TÜV SÜD certification body for medical devices class IIa/medical device software for ophthalmology.

This gives RetInSight a unique selling proposition and opens up an outstanding market position in the field of AI-assisted retinal biomarker image analysis.

Heidelberg Engineering and RetInSight to offer AI-based OCT fluid quantification solution

Fundus autofluorescence and optical coherence tomography

[The Royal Collage of Ophthalmologists, 2021]
Authors: Schmidt-Erfurth U, Bui P, Reiter G, Fabianska M, Waldstein S, Grechenig C, Bogunovic H, Arikan M.

AI-based monitoring of retinal fluid in disease activity and under therapy.

[Prog Retin Eye Res. 2021; Article in press]
Authors: 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]
Authors: 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]
Authors: Schmidt-Erfurth U, Waldstein SM.

Fully Automated Detection and Quantification of Macular Fluid in OCT Using Deep Learning.

[Ophthalmology. 2018;125(4):549-558]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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]
Authors: 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.