2020 - IEEE Fellow For contributions to the application of artificial intelligence methods in diabetic retinopathy
Michael D. Abràmoff focuses on Artificial intelligence, Diabetic retinopathy, Computer vision, Retinal and Retina. His work in the fields of Artificial intelligence, such as Feature, Medical imaging and Image texture, intersects with other areas such as Reference standards and Filter bank. His Diabetic retinopathy study integrates concerns from other disciplines, such as Retinopathy, Internal medicine, Receiver operating characteristic and Fundus.
Computer vision is frequently linked to Optic disc in his study. His research integrates issues of Image processing, Optical coherence tomography and Vessel segmentation in his study of Retinal. The concepts of his Retina study are interwoven with issues in Feature vector, Macular degeneration and Optic nerve.
Michael D. Abràmoff mostly deals with Artificial intelligence, Ophthalmology, Retinal, Computer vision and Optical coherence tomography. His studies deal with areas such as Fundus and Pattern recognition as well as Artificial intelligence. His research in Retinal intersects with topics in Diabetic retinopathy, Retina, Optics, Internal medicine and Biomedical engineering.
His research investigates the link between Diabetic retinopathy and topics such as Retinopathy that cross with problems in Eye disease. Optic disk is closely connected to Optic disc in his research, which is encompassed under the umbrella topic of Computer vision. His Optical coherence tomography course of study focuses on Glaucoma and Optic nerve.
Diabetic retinopathy, Artificial intelligence, Ophthalmology, Optical coherence tomography and Retinal are his primary areas of study. His Diabetic retinopathy study combines topics from a wide range of disciplines, such as Retinopathy, Telemedicine, Pediatrics and Type 2 diabetes. His Artificial intelligence research integrates issues from Computer vision and Pattern recognition.
His Nerve fiber layer and Macular degeneration study, which is part of a larger body of work in Ophthalmology, is frequently linked to In patient, bridging the gap between disciplines. His work deals with themes such as Choroid, Glaucoma and Medical imaging, which intersect with Optical coherence tomography. His Retinal study focuses on Fundus in particular.
His main research concerns Diabetic retinopathy, Artificial intelligence, Ophthalmology, Diabetes mellitus and Optical coherence tomography. Michael D. Abràmoff has included themes like Retinopathy, Primary care, Type 2 diabetes, Disease and Pediatrics in his Diabetic retinopathy study. His work carried out in the field of Artificial intelligence brings together such families of science as Diabetic retinopathy screening and Machine learning.
He has researched Ophthalmology in several fields, including Meta-analysis, Tomography and Confidence interval. He interconnects Retina, Neuroscience and Neurodegeneration in the investigation of issues within Diabetes mellitus. His biological study spans a wide range of topics, including Fluorescein angiography and Medical imaging.
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Image processing with ImageJ
Michael D. Abràmoff;Paulo J. Magalhães;Sunanda J. Ram.
Biophotonics international (2004)
Ridge-based vessel segmentation in color images of the retina
J. Staal;M.D. Abramoff;M. Niemeijer;M.A. Viergever.
IEEE Transactions on Medical Imaging (2004)
Retinal Imaging and Image Analysis
M D Abràmoff;M K Garvin;M Sonka.
IEEE Reviews in Biomedical Engineering (2010)
Comparative study of retinal vessel segmentation methods on a new publicly available database
Meindert Niemeijer;Meindert Niemeijer;Joes Staal;Bram van Ginneken;Marco Loog.
Medical Imaging 2004: Image Processing (2004)
Automatic detection of red lesions in digital color fundus photographs
M. Niemeijer;B. van Ginneken;J. Staal;M.S.A. Suttorp-Schulten.
IEEE Transactions on Medical Imaging (2005)
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.
Investigative Ophthalmology & Visual Science (2016)
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.
IEEE Transactions on Medical Imaging (2009)
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.
npj Digital Medicine (2018)
Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs
Meindert Niemeijer;Bram van Ginneken;Michael J Cree;Atsushi Mizutani.
IEEE Transactions on Medical Imaging (2010)
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.
Investigative Ophthalmology & Visual Science (2007)
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