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Michael D. Abràmoff

Michael D. Abràmoff

D-Index & Metrics

Computer Science

D-Index
74
Citations
44915
World Ranking
1446
National Ranking
752

Research.com Recognitions

  • 2020 - IEEE Fellow For contributions to the application of artificial intelligence methods in diabetic retinopathy

Overview

Michael D. Abràmoff is affiliated with the University of Iowa in the United States. Their research primarily focuses on the intersection of medicine and technology, particularly within the field of ophthalmology. They have contributed extensively to the study of retinal imaging and analysis, retinal diseases and treatments, and artificial intelligence applications in healthcare.

The main fields of study for Michael D. Abràmoff include Medicine, with a strong emphasis on subfields such as Ophthalmology, Radiology, Nuclear Medicine and Imaging, Health Informatics, Public Health, Environmental and Occupational Health, and Health Information Management.

The key topics covered in their research are:

  • Retinal Imaging and Analysis
  • Retinal Diseases and Treatments
  • Artificial Intelligence in Healthcare and Education
  • Retinal and Optic Conditions
  • Glaucoma and retinal disorders
  • Artificial Intelligence in Healthcare
  • Healthcare cost, quality, practices

Michael D. Abràmoff has published in several notable academic journals. Frequent venues of publication include:

  • npj Digital Medicine
  • Diabetes
  • The American Journal of Bioethics
  • Ophthalmology
  • Translational Vision Science & Technology

Several recent papers illustrate the scope and focus of Abràmoff's research:

  • "Identifying Ethical Considerations for Machine Learning Healthcare Applications" (2020), published in The American Journal of Bioethics
  • "Considerations for addressing bias in artificial intelligence for health equity" (2023), published in npj Digital Medicine
  • "Current Challenges and Barriers to Real-World Artificial Intelligence Adoption for the Healthcare System, Provider, and the Patient" (2020), published in Translational Vision Science & Technology
  • "A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI" (2021), published in Nature Medicine
  • "Lessons Learned About Autonomous AI: Finding a Safe, Efficacious, and Ethical Path Through the Development Process" (2020), published in American Journal of Ophthalmology

Michael D. Abràmoff has collaborated frequently with several coauthors, including Roomasa Channa, Risa M. Wolf, Michael F. Chiang, Harold P. Lehmann, and Danton Char.

Their contributions have been recognized with the award of IEEE Fellow in 2020 for work related to the application of artificial intelligence methods in diabetic retinopathy.

Best Publications

  • Image processing with ImageJ

    Michael D. Abràmoff;Paulo J. Magalhães;Sunanda J. Ram

  • Ridge-based vessel segmentation in color images of the retina

    J. Staal;M.D. Abramoff;M. Niemeijer;M.A. Viergever

  • Retinal Imaging and Image Analysis

    M D Abràmoff;M K Garvin;M Sonka

  • Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices

    Michael D. Abràmoff;Philip T. Lavin;Michele Birch;Nilay Shah

  • Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning.

    Michael David Abràmoff;Michael David Abràmoff;Yiyue Lou;Ali Erginay;Warren Clarida

  • Comparative study of retinal vessel segmentation methods on a new publicly available database

    Meindert Niemeijer;Meindert Niemeijer;Joes Staal;Bram van Ginneken;Marco Loog

  • Automated 3-D Intraretinal Layer Segmentation of Macular Spectral-Domain Optical Coherence Tomography Images

    M.K. Garvin;M.D. Abramoff;Xiaodong Wu;S.R. Russell

  • Automatic detection of red lesions in digital color fundus photographs

    M. Niemeijer;B. van Ginneken;J. Staal;M.S.A. Suttorp-Schulten

  • Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs

    Meindert Niemeijer;Bram van Ginneken;Michael J Cree;Atsushi Mizutani

  • Automated Detection and Differentiation of Drusen, Exudates, and Cotton-Wool Spots in Digital Color Fundus Photographs for Diabetic Retinopathy Diagnosis

    Meindert Niemeijer;Meindert Niemeijer;Meindert Niemeijer;Bram van Ginneken;Bram van Ginneken;Bram van Ginneken;Stephen R. Russell;Stephen R. Russell;Maria S. A. Suttorp-Schulten

  • Automated Analysis of Retinal Images for Detection of Referable Diabetic Retinopathy

    Michael D. Abràmoff;James C. Folk;Dennis P. Han;Jonathan D. Walker

  • End-to-End Adversarial Retinal Image Synthesis

    Pedro Costa;Adrian Galdran;Maria Ines Meyer;Meindert Niemeijer

  • Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search

    M.K. Garvin;M.D. Abramoff;R. Kardon;S.R. Russell

  • Identifying Ethical Considerations for Machine Learning Healthcare Applications

    Danton S. Char;Michael D. Abràmoff;Chris Feudtner;Chris Feudtner

  • Evaluation of a System for Automatic Detection of Diabetic Retinopathy From Color Fundus Photographs in a Large Population of Patients With Diabetes

    Michael D. Abràmoff;Meindert Niemeijer;Maria S.A. Suttorp-Schulten;Max A. Viergever

  • Artificial intelligence for diabetic retinopathy screening: a review

    Andrzej Grzybowski;Piotr Brona;Gilbert Lim;Gilbert Lim;Paisan Ruamviboonsuk

  • Automated early detection of diabetic retinopathy.

    Michael D. Abràmoff;Michael D. Abràmoff;Michael D. Abràmoff;Joseph M. Reinhardt;Stephen R. Russell;Stephen R. Russell;James C. Folk;James C. Folk

  • Multiscale AM-FM Methods for Diabetic Retinopathy Lesion Detection

    C. Agurto;V. Murray;E. Barriga;S. Murillo

  • Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features.

    Michael D. Abràmoff;Michael D. Abràmoff;Michael D. Abràmoff;Wallace L. M. Alward;Wallace L. M. Alward;Emily C. Greenlee;Emily C. Greenlee;Lesya Shuba

  • Fast detection of the optic disc and fovea in color fundus photographs

    Meindert Niemeijer;Meindert Niemeijer;Michael D. Abràmoff;Michael D. Abràmoff;Bram van Ginneken

  • Segmentation of the Optic Disc, Macula and Vascular Arch in Fundus Photographs

    M. Niemeijer;M.D. Abramoff;B. van Ginneken

  • Automatic Detection of Red Lesions in Digital Color

    Meindert Niemeijer;Bram van Ginneken;Joes Staal;Maria S. A. Suttorp-Schulten

Frequent Co-Authors

Milan Sonka
Milan Sonka University of Iowa
Meindert Niemeijer
Meindert Niemeijer Digital Diagnostics Inc.
Randy H. Kardon
Randy H. Kardon University of Iowa
Joseph M. Reinhardt
Joseph M. Reinhardt University of Iowa
Edwin M. Stone
Edwin M. Stone University of Iowa
Todd E. Scheetz
Todd E. Scheetz University of Iowa
Robert F. Mullins
Robert F. Mullins University of Iowa
Bram van Ginneken
Bram van Ginneken Radboud University
John H. Fingert
John H. Fingert University of Iowa

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