Hideharu Ohsugi

1.1k total citations
16 papers, 720 citations indexed

About

Hideharu Ohsugi is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Epidemiology. According to data from OpenAlex, Hideharu Ohsugi has authored 16 papers receiving a total of 720 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Ophthalmology, 13 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Epidemiology. Recurrent topics in Hideharu Ohsugi's work include Retinal Diseases and Treatments (9 papers), Retinal Imaging and Analysis (8 papers) and Glaucoma and retinal disorders (8 papers). Hideharu Ohsugi is often cited by papers focused on Retinal Diseases and Treatments (9 papers), Retinal Imaging and Analysis (8 papers) and Glaucoma and retinal disorders (8 papers). Hideharu Ohsugi collaborates with scholars based in Japan and United States. Hideharu Ohsugi's co-authors include Hitoshi Tabuchi, Hiroki Enno, Naofumi Ishitobi, Yasushi Ikuno, Hiroki Masumoto, Tomofusa Yamauchi, Yoshinori Mitamura, Daisuke Nagasato, Yoshiaki Kiuchi and Shunsuke Nakakura and has published in prestigious journals such as PLoS ONE, Scientific Reports and American Journal of Ophthalmology.

In The Last Decade

Hideharu Ohsugi

16 papers receiving 697 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hideharu Ohsugi Japan 15 600 570 135 43 42 16 720
Alfonso Antón Spain 15 896 1.5× 790 1.4× 93 0.7× 111 2.6× 58 1.4× 58 1.0k
Daisuke Nagasato Japan 14 443 0.7× 389 0.7× 64 0.5× 19 0.4× 38 0.9× 35 553
Naofumi Ishitobi Japan 10 350 0.6× 394 0.7× 35 0.3× 48 1.1× 41 1.0× 13 470
Jost Lennart Lauermann Germany 13 585 1.0× 612 1.1× 50 0.4× 33 0.8× 119 2.8× 29 725
Yuri Fujino Japan 19 1.2k 1.9× 1.1k 1.9× 127 0.9× 110 2.6× 69 1.6× 72 1.3k
Sunee Chansangpetch Thailand 14 407 0.7× 361 0.6× 40 0.3× 29 0.7× 48 1.1× 56 482
Hiroki Masumoto Japan 13 340 0.6× 361 0.6× 27 0.2× 41 1.0× 39 0.9× 18 470
Junkichi Yamagami Japan 13 601 1.0× 487 0.9× 28 0.2× 39 0.9× 44 1.0× 25 656
Maximilian Treder Germany 12 504 0.8× 517 0.9× 33 0.2× 33 0.8× 105 2.5× 34 642
Weihong Yu China 14 473 0.8× 473 0.8× 29 0.2× 47 1.1× 32 0.8× 51 606

Countries citing papers authored by Hideharu Ohsugi

Since Specialization
Citations

This map shows the geographic impact of Hideharu Ohsugi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hideharu Ohsugi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideharu Ohsugi more than expected).

Fields of papers citing papers by Hideharu Ohsugi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hideharu Ohsugi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hideharu Ohsugi. The network helps show where Hideharu Ohsugi may publish in the future.

Co-authorship network of co-authors of Hideharu Ohsugi

This figure shows the co-authorship network connecting the top 25 collaborators of Hideharu Ohsugi. A scholar is included among the top collaborators of Hideharu Ohsugi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hideharu Ohsugi. Hideharu Ohsugi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Tabuchi, Hitoshi, Daisuke Nagasato, Hiroki Masumoto, et al.. (2020). Accuracy of a deep convolutional neural network in the detection of myopic macular diseases using swept-source optical coherence tomography. PLoS ONE. 15(4). e0227240–e0227240. 48 indexed citations
2.
Masumoto, Hiroki, Hitoshi Tabuchi, Shunsuke Nakakura, et al.. (2019). Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images. PeerJ. 7. e6900–e6900. 43 indexed citations
3.
Nagasato, Daisuke, Hitoshi Tabuchi, Hideharu Ohsugi, et al.. (2019). Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion. International Journal of Ophthalmology. 12(1). 94–99. 46 indexed citations
4.
Masumoto, Hiroki, Hitoshi Tabuchi, Tsuyoshi Yoneda, et al.. (2019). Severity Classification of Conjunctival Hyperaemia by Deep Neural Network Ensembles. Journal of Ophthalmology. 2019. 1–10. 19 indexed citations
5.
Nagasato, Daisuke, Hitoshi Tabuchi, Hideharu Ohsugi, et al.. (2018). Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy. Journal of Ophthalmology. 2018. 1–6. 49 indexed citations
6.
Tabuchi, Hitoshi, Hideharu Ohsugi, Hiroki Enno, et al.. (2018). Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration. International Ophthalmology. 39(6). 1269–1275. 72 indexed citations
7.
Tabuchi, Hitoshi, et al.. (2018). Comparison between support vector machine and deep learning, machine-learning technologies for detecting epiretinal membrane using 3D-OCT. International Ophthalmology. 39(8). 1871–1877. 37 indexed citations
8.
Nagasawa, Toshihiko, Hitoshi Tabuchi, Hiroki Masumoto, et al.. (2018). Accuracy of deep learning, a machine learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting idiopathic macular holes. PeerJ. 6. e5696–e5696. 31 indexed citations
9.
Ohsugi, Hideharu, et al.. (2018). MORPHOLOGIC CHARACTERISTICS OF MACULAR HOLE AND MACULAR HOLE RETINAL DETACHMENT ASSOCIATED WITH EXTREME MYOPIA. Retina. 39(7). 1312–1318. 14 indexed citations
10.
Ohsugi, Hideharu, Hitoshi Tabuchi, Hiroki Enno, & Naofumi Ishitobi. (2017). Accuracy of deep learning, a machine-learning technology, using ultra–wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment. Scientific Reports. 7(1). 9425–9425. 89 indexed citations
11.
Ohsugi, Hideharu, et al.. (2017). Axial length changes in highly myopic eyes and influence of myopic macular complications in Japanese adults. PLoS ONE. 12(7). e0180851–e0180851. 37 indexed citations
12.
Ohsugi, Hideharu, et al.. (2014). Morphologic Characteristics of Macular Complications of a Dome-Shaped Macula Determined by Swept-Source Optical Coherence Tomography. American Journal of Ophthalmology. 158(1). 162–170.e1. 86 indexed citations
13.
Yamauchi, Tomofusa, et al.. (2013). Comparison of Visual Performance of Multifocal Intraocular Lenses with Same Material Monofocal Intraocular Lenses. PLoS ONE. 8(6). e68236–e68236. 55 indexed citations
14.
Ohsugi, Hideharu, Yasushi Ikuno, Hitoshi Imamura, et al.. (2013). Changes in choroidal thickness after cataract surgery. Journal of Cataract & Refractive Surgery. 40(2). 184–191. 54 indexed citations
15.
Ohsugi, Hideharu, et al.. (2013). 3-D Choroidal Thickness Maps from EDI-OCT in Highly Myopic Eyes. Optometry and Vision Science. 90(6). 599–606. 32 indexed citations
16.
Tabuchi, Hitoshi, et al.. (2011). Effects of corneal thickness and axial length on intraocular pressure and ocular pulse amplitude before and after cataract surgery. Canadian Journal of Ophthalmology. 46(3). 242–246. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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