Hideharu Ohsugi

Kobe, Japan

Last Updated: 09/26/2026

Save publications for later

Sign Up

Not sure about your diagnosis?

Check Your Symptoms

Found 16 publications

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.

Journal: PloS one

Published: December 13, 2019

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.

Journal: PeerJ

Published: December 05, 2018

Severity Classification of Conjunctival Hyperaemia by Deep Neural Network Ensembles.

Severity Classification of Conjunctival Hyperaemia by Deep Neural Network Ensembles.

Journal: Journal of ophthalmology

Published: November 27, 2018

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.

Journal: Journal of ophthalmology

Published: September 05, 2018

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.

Journal: International journal of ophthalmology

Published: August 18, 2018

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.

Journal: International ophthalmology

Published: June 28, 2018

Comparison between support vector machine and deep learning, machine-learning technologies for detecting epiretinal membrane using 3D-OCT.

Comparison between support vector machine and deep learning, machine-learning technologies for detecting epiretinal membrane using 3D-OCT.

Journal: International ophthalmology

Published: April 06, 2018

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.

Journal: PeerJ

Published: March 26, 2018

MORPHOLOGIC CHARACTERISTICS OF MACULAR HOLE AND MACULAR HOLE RETINAL DETACHMENT ASSOCIATED WITH EXTREME MYOPIA.

MORPHOLOGIC CHARACTERISTICS OF MACULAR HOLE AND MACULAR HOLE RETINAL DETACHMENT ASSOCIATED WITH EXTREME MYOPIA.

Journal: Retina (Philadelphia, Pa.)

Published: March 20, 2018

Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration.

Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration.

Journal: International ophthalmology

Published: January 29, 2018

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.

Journal: Scientific reports

Published: April 10, 2017

Axial length changes in highly myopic eyes and influence of myopic macular complications in Japanese adults.

Axial length changes in highly myopic eyes and influence of myopic macular complications in Japanese adults.

Journal: PloS one

Published: January 31, 2017

Showing 1-12 of 16

Last Updated: 09/26/2026