Risultati della ricerca - Hitoshi Tabuchi

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  1. 1
    Accuracy of deep learning, a machine-learning technology, using ultra–wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment

    Accuracy of deep learning, a machine-learning technology, using ultra–wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment di Hideharu Ohsugi, Hitoshi Tabuchi, Hiroki Enno, Naofumi Ishitobi

    Pubblicazione 2017
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  2. 2
    Real-Time Extraction of Important Surgical Phases in Cataract Surgery Videos

    Real-Time Extraction of Important Surgical Phases in Cataract Surgery Videos di Shoji Morita, Hitoshi Tabuchi, Hiroki Masumoto, Tomofusa Yamauchi, Naotake Kamiura

    Pubblicazione 2019
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    Artigo
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  3. 3
    Comparison of Visual Performance of Multifocal Intraocular Lenses with Same Material Monofocal Intraocular Lenses

    Comparison of Visual Performance of Multifocal Intraocular Lenses with Same Material Monofocal Intraocular Lenses di Tomofusa Yamauchi, Hitoshi Tabuchi, Kosuke Takase, Hideharu Ohsugi, Zaigen Ohara, Yoshiaki Kiuchi

    Pubblicazione 2013
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  4. 4
    Agreement among Goldmann applanation tonometer, iCare, and Icare PRO rebound tonometers; non-contact tonometer; and Tonopen XL in healthy elderly subjects

    Agreement among Goldmann applanation tonometer, iCare, and Icare PRO rebound tonometers; non-contact tonometer; and Tonopen XL in healthy elderly subjects di Yoshitake Kato, Shunsuke Nakakura, Naoko Matsuo, Kayo Yoshitomi, Marina Handa, Hitoshi Tabuchi, Yoshiaki Kiuchi

    Pubblicazione 2017
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  5. 5
    Accuracy of deep learning, a machine learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting idiopathic macular holes

    Accuracy of deep learning, a machine learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting idiopathic macular holes di Toshihiko Nagasawa, Hitoshi Tabuchi, Hiroki Masumoto, Hiroki Enno, Masanori Niki, Hideharu Ohsugi, Yoshinori Mitamura

    Pubblicazione 2018
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    Artigo
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  6. 6
    Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images

    Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images di Hiroki Masumoto, Hitoshi Tabuchi, Shunsuke Nakakura, Hideharu Ohsugi, Hiroki Enno, Naofumi Ishitobi, Eiko Ohsugi, Yoshinori Mitamura

    Pubblicazione 2019
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  7. 7
    Automated detection of a nonperfusion area caused by retinal vein occlusion in optical coherence tomography angiography images using deep learning

    Automated detection of a nonperfusion area caused by retinal vein occlusion in optical coherence tomography angiography images using deep learning di Daisuke Nagasato, Hitoshi Tabuchi, Hiroki Masumoto, Hiroki Enno, Naofumi Ishitobi, Masahiro Kameoka, Masanori Niki, Yoshinori Mitamura

    Pubblicazione 2019
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  8. 8
    Accuracy of a deep convolutional neural network in the detection of myopic macular diseases using swept-source optical coherence tomography

    Accuracy of a deep convolutional neural network in the detection of myopic macular diseases using swept-source optical coherence tomography di Takahiro Sogawa, Hitoshi Tabuchi, Daisuke Nagasato, Hiroki Masumoto, Yasushi Ikuno, Hideharu Ohsugi, Naofumi Ishitobi, Yoshinori Mitamura

    Pubblicazione 2020
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  9. 9
    The Relationship between Corvis ST Tonometry Measured Corneal Parameters and Intraocular Pressure, Corneal Thickness and Corneal Curvature

    The Relationship between Corvis ST Tonometry Measured Corneal Parameters and Intraocular Pressure, Corneal Thickness and Corneal Curvature di Ryo Asaoka, Shunsuke Nakakura, Hitoshi Tabuchi, Hiroshi Murata, Yoshitaka Nakao, Noriko Ihara, Ulfah Rimayanti, Makoto Aihara, Yoshiaki Kiuchi

    Pubblicazione 2015
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  10. 10
    Macular Choroidal Thickness and Volume in Healthy Pediatric Individuals Measured by Swept-Source Optical Coherence Tomography

    Macular Choroidal Thickness and Volume in Healthy Pediatric Individuals Measured by Swept-Source Optical Coherence Tomography di Toshihiko Nagasawa, Yoshinori Mitamura, Takashi Katome, Kayo Shinomiya, Takeshi Naito, Daisuke Nagasato, Yukiko Shimizu, Hitoshi Tabuchi, Yoshiaki Kiuchi

    Pubblicazione 2013
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  11. 11
    Accuracy of ultrawide-field fundus ophthalmoscopy-assisted deep learning for detecting treatment-naïve proliferative diabetic retinopathy

    Accuracy of ultrawide-field fundus ophthalmoscopy-assisted deep learning for detecting treatment-naïve proliferative diabetic retinopathy di Toshihiko Nagasawa, Hitoshi Tabuchi, Hiroki Masumoto, Hiroki Enno, Masanori Niki, Zaigen Ohara, Yuki Yoshizumi, Hideharu Ohsugi, Yoshinori Mitamura

    Pubblicazione 2019
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    Carta
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  12. 12
    Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion

    Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion di Daisuke Nagasato, Hitoshi Tabuchi, Hideharu Ohsugi, Hiroki Masumoto, Hiroki Enno, Naofumi Ishitobi, Tomoaki Sonobe, Masahiro Kameoka, Masanori Niki, Yoshinori Mitamura

    Pubblicazione 2019
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  13. 13
    Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy

    Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy di Daisuke Nagasato, Hitoshi Tabuchi, Hideharu Ohsugi, Hiroki Masumoto, Hiroki Enno, Naofumi Ishitobi, Tomoaki Sonobe, Masahiro Kameoka, Masanori Niki, Ken Hayashi, Yoshinori Mitamura

    Pubblicazione 2018
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  14. 14
    Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images

    Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images di Hitoshi Tabuchi, Justin Engelmann, Fumiatsu Maeda, Ryo Nishikawa, Toshihiko Nagasawa, Tomofusa Yamauchi, Mao Tanabe, Masahiro Akada, Keita Kihara, Yasuyuki Nakae, Yoshiaki Kiuchi, Miguel O. Bernabéu

    Pubblicazione 2024
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  15. 15
    Estimation of Visual Function Using Deep Learning From Ultra-Widefield Fundus Images of Eyes With Retinitis Pigmentosa

    Estimation of Visual Function Using Deep Learning From Ultra-Widefield Fundus Images of Eyes With Retinitis Pigmentosa di Daisuke Nagasato, Takahiro Sogawa, Mao Tanabe, Hitoshi Tabuchi, Shogo Numa, Akio Oishi, Hanako Ohashi Ikeda, Akitaka Tsujikawa, Tadao Maeda, Masayo Takahashi, Nana Ito, Gen Miura, Terumi Shinohara, Mariko Egawa, Yoshinori Mitamura

    Pubblicazione 2023
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