Hideharu Ohsugi - Concepedia

Author

Hideharu Ohsugi

Research Organization for Information Science and Technology ORCID

Also Known As

H. Ohsugi, Hideharu Ohsugi

Publications

1.1K

Citations

H-Index

Concepts

All Affiliations

Research Organization for Information Science and Technology Tokushima University Hiroshima University Hyogo Brain and Heart Center Yazaki (United States)

About

Hideharu Ohsugi is an author at Research Organization for Information Science and Technology specializing in ophthalmology, deep learning, and engineering.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	4	4	253
2	Health Sciences	2	2	153
3	Medicine	2	2	80
4	Biomedical Engineering	2	2	141
5	Neurology	1	1	68

Hideharu Ohsugi

Publications

986

Citations

H-Index

Page 1

	Year	Citations
Accuracy of deep learning, a machine-learning technology, using ultra–wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment Hideharu Ohsugi, Hitoshi Tabuchi, Hiroki Enno, Scientific Reports	2017	149
Morphologic Characteristics of Macular Complications of a Dome-Shaped Macula Determined by Swept-Source Optical Coherence Tomography Hideharu Ohsugi, Yasushi Ikuno, Kanako Oshima, American Journal of Ophthalmology Ocular DiseaseOphthalmologyMedical ImagingDome-shaped MaculaMacular Complications	2014	109
Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration Shinji Matsuba, Hitoshi Tabuchi, Hideharu Ohsugi, International Ophthalmology Ocular DiseaseEngineeringMachine LearningOphthalmologyAge-related Diseases	2018	90
Comparison of Visual Performance of Multifocal Intraocular Lenses with Same Material Monofocal Intraocular Lenses Tomofusa Yamauchi, Hitoshi Tabuchi, Kosuke Takase, PLoS ONE	2013	75
Changes in choroidal thickness after cataract surgery Hideharu Ohsugi, Yasushi Ikuno, Zaigen Ohara, Journal of Cataract & Refractive Surgery	2013	73
Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy Daisuke Nagasato, Hitoshi Tabuchi, Hideharu Ohsugi, Journal of Ophthalmology	2018	70
Accuracy of a deep convolutional neural network in the detection of myopic macular diseases using swept-source optical coherence tomography Takahiro Sogawa, Hitoshi Tabuchi, Daisuke Nagasato, PLoS ONE Artificial IntelligenceOcular DiseaseEngineeringRetinaMedical Imaging	2020	68
Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion Daisuke Nagasato, Hitoshi Tabuchi, Hideharu Ohsugi, International Journal of Ophthalmology	2019	56
Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images Hiroki Masumoto, Hitoshi Tabuchi, Shunsuke Nakakura, PeerJ	2019	55
Comparison between support vector machine and deep learning, machine-learning technologies for detecting epiretinal membrane using 3D-OCT Tomoaki Sonobe, Hitoshi Tabuchi, Hideharu Ohsugi, International Ophthalmology Machine-learning TechnologiesImage ClassificationImage AnalysisMachine VisionOphthalmology	2018	51

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