1,323 Hits in 7.9 sec

Prediction of Sex and Age from Macular Optical Coherence Tomography Images and Feature Analysis Using Deep Learning [article]

Kuan-Ming Chueh, Yi-Ting Hsieh, Homer H. Chen, I-Hsin Ma, Sheng-Lung Huang
2020 medRxiv   pre-print
In this study, deep learning was applied to distinguish sex and age from macular optical coherence tomography (OCT) images of 3134 persons and achieved a sex prediction accuracy of 85.6 ± 2.1% and an age  ...  sex-related information than en face fundus images, and 3) the age-related characteristics of the macula are on the whole layers of the retina, not just the choroid.  ...  In this study, deep learning to train CNN was used to predict sex and age according to macular OCT images, and then Grad-CAM was used to explore the sex and age-related features from different layers of  ... 
doi:10.1101/2020.12.23.20248805 fatcat:lghzjbkz75bnxfedj72tcme44a

Prediction of Cardiovascular Parameters With Supervised Machine Learning From Singapore "I" Vessel Assessment and OCT-Angiography: A Pilot Study

Louis Arnould, Charles Guenancia, Abderrahmane Bourredjem, Christine Binquet, Pierre-Henry Gabrielle, Pétra Eid, Florian Baudin, Ryo Kawasaki, Yves Cottin, Catherine Creuzot-Garcher, Sabir Jacquir
2021 Translational Vision Science & Technology  
measured with fundus photography and optical coherence tomography - angiography (OCT-A) scans (alone and combined).  ...  Small data set of quantitative retinal vascular parameters with fundus and with OCT-A can be used with ML learning to predict cardiovascular parameters.  ...  Acknowledgments The authors are grateful to Linda Northrup who copyedited this manuscript and to Arnaud Attye for his careful review.  ... 
doi:10.1167/tvst.10.13.20 pmid:34767626 pmcid:PMC8590163 fatcat:golcx7f3lndlfmopdsppgqhaga

A deep learning approach to predict visual field using optical coherence tomography

Keunheung Park, Jinmi Kim, Jiwoong Lee, Ireneusz Grulkowski
2020 PLoS ONE  
We developed a deep learning architecture based on Inception V3 to predict visual field using optical coherence tomography (OCT) imaging and evaluated its performance.  ...  The deep learning method effectively predicted the visual field 24-2 using the combined OCT image.  ...  learning approach to predict visual field using optical coherence tomography.  ... 
doi:10.1371/journal.pone.0234902 pmid:32628672 fatcat:e626j4xeqbhjdaqrxfocvmxgmi

Assessment of patient specific information in the wild on fundus photography and optical coherence tomography

Marion R. Munk, Thomas Kurmann, Pablo Márquez-Neila, Martin S. Zinkernagel, Sebastian Wolf, Raphael Sznitman
2021 Scientific Reports  
Deep learning models were trained to predict the patient's age and sex from fundus images, OCT cross sections and OCT volumes.  ...  We conclude that deep learning based methods are capable of classifying the patient's sex and age from color fundus photography and OCT for a broad spectrum of patients irrespective of underlying disease  ...  It is also applied to automatically assess image quality, to quantify and segment retinal structures and to improve image quality of color fundus images, optical coherence tomography (OCT) and OCT angiography  ... 
doi:10.1038/s41598-021-86577-5 pmid:33883573 pmcid:PMC8060417 fatcat:hehlrkeh3fanjmbbevbmk66twq

Automated diagnosis and staging of Fuchs' endothelial cell corneal dystrophy using deep learning

Taher Eleiwa, Amr Elsawy, Eyüp Özcan, Mohamed Abou Shousha
2020 Eye and Vision  
FECD eyes using high-definition optical coherence tomography (HD-OCT).  ...  A total of 18,720 anterior segment optical coherence tomography (AS-OCT) images (9180 healthy; 5400 early-stage FECD; 4140 late-stage FECD) of 104 eyes (81 patients) were used to develop and validate a  ...  Fig. 1 1 Flow-chart illustrating the number of anterior segment optical coherence tomography (AS-OCT) images used to develop, train and test the deep learning algorithm Fig. 3 3 Receiver operating characteristic  ... 
doi:10.1186/s40662-020-00209-z pmid:32884962 pmcid:PMC7460770 fatcat:on2fyegvq5a4niobxdm76rwfh4

Deep Learning Model Based on 3D Optical Coherence Tomography Images for the Automated Detection of Pathologic Myopia

So-Jin Park, Taehoon Ko, Chan-Kee Park, Yong-Chan Kim, In-Young Choi
2022 Diagnostics  
Mary's Hospital from January 2012 to May 2020. To automatically diagnose pathologic myopia, a deep learning model was developed using 3D optical coherence tomography images.  ...  The study was conducted using 367 eyes of patients who underwent optical coherence tomography tests at the Ophthalmology Department of Incheon St. Mary's Hospital and Seoul St.  ...  Acknowledgments: We thank Ji Ho Park, Ji Hyoung Jang, and Byung Wook Kim for helping us analyze the data. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/diagnostics12030742 pmid:35328292 pmcid:PMC8947335 fatcat:hljoiztl4bbuzhswh4wu5ye2oi

Front Matter: Volume 11583

Jorge Brieva, Natasha Lepore, Eduardo Romero Castro, Marius G. Linguraru
2020 16th International Symposium on Medical Information Processing and Analysis  
the UK Biobank DEEP LEARNING 09 Deep transfer learning of brain shape morphometry predicts Body Mass Index (BMI) in the UK Biobank 11583 0A Deep-learning based tractography for neonates 11583 0B Deep  ...  in healthy and Alzheimer subjects BRAIN IMAGING II 11583 06 Sex-dependent age trajectories of subcortical brain structures: analysis of large-scale percentile models and shape morphometry 11583 07 Advanced  ...  0H Segmentation of retinal fluids and hyperreflective foci using deep learning approach in optical coherence tomography scans 11583 0I Segmentation of exudates in fundus images applying color mathematical  ... 
doi:10.1117/12.2587203 fatcat:qv23dgmml5hqdl64xfgvfi4loe

Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy [article]

David Le, Minhaj Alam, Cham Yao, Jennifer I. Lim, R.V.P. Chan, Devrim Toslak, Xincheng Yao
2019 arXiv   pre-print
Purpose: To test the feasibility of using deep learning for optical coherence tomography angiography (OCTA) detection of diabetic retinopathy (DR).  ...  Methods: A deep learning convolutional neural network (CNN) architecture VGG16 was employed for this study.  ...  QUANTITATIVE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY FEATURES FOR OBJECTIVE CLASSIFICATION AND STAGING OF DIABETIC RETINOPATHY RETINA 2019. 25.  ... 
arXiv:1910.01796v1 fatcat:5j77wigdjbdsxlhp4syizxjmem

Macular Ganglion Cell-Inner Plexiform Layer Thickness Prediction from Red-free Fundus Photography using Hybrid Deep Learning Model

Jinho Lee, Young Kook Kim, Ahnul Ha, Sukkyu Sun, Yong Woo Kim, Jin-Soo Kim, Jin Wook Jeoung, Ki Ho Park
2020 Scientific Reports  
A total of 789 pairs of RNFLPs and spectral domain-optical coherence tomography (SD-OCT) scans for 431 eyes of 259 participants (183 eyes of 114 healthy controls, 68 eyes of 46 glaucoma suspects, and 180  ...  We developed a hybrid deep learning model (HDLM) algorithm that quantitatively predicts macular ganglion cell-inner plexiform layer (mGCIPL) thickness from red-free retinal nerve fiber layer photographs  ...  The dataset generated during the current study is available from the corresponding author on reasonable request.  ... 
doi:10.1038/s41598-020-60277-y pmid:32094401 pmcid:PMC7039950 fatcat:f2jxlrhztvdbvlqsszbtw552be

Prior Optic Neuritis Detection on Peripapillary Ring Scans using Deep Learning [article]

Seyedamirhosein Motamedi, Sunil Kumar Yadav, Rachel Kenney, Ting-Yi Lin, Josef Kauer-Bonin, Hanna Gwendolyn Zimmermann, Steven Galetta, Laura Balcer, Friedemann Paul, Alexander U Brandt
2022 medRxiv   pre-print
Peripapillary retinal nerve fiber layer (pRNFL) thickness as measured by optical coherence tomography (OCT) distinguishes eyes with a prior history of acute optic neuritis (ON) and may provide evidence  ...  Objective: To investigate whether a deep learning (DL)-based network can distinguish between eyes with prior ON and healthy control (HC) eyes using peripapillary ring scans.  ...  Acknowledgment This study was supported in part by Berlin Institute of Health (project "DEEP-Neuroretina" to A.U. Brandt).  ... 
doi:10.1101/2022.04.27.22274388 fatcat:vzjxq4ag45dbzkmcavxp7dxqfa

Artificial Intelligence and OCT Angiography in Full Thickness Macular Hole. New Developments for Personalized Medicine

Stanislao Rizzo, Alfonso Savastano, Jacopo Lenkowicz, Maria Cristina Savastano, Luca Boldrini, Daniela Bacherini, Benedetto Falsini, Vincenzo Valentini
2021 Diagnostics  
Purpose: To evaluate the 1-year visual acuity predictive performance of an artificial intelligence (AI) based model applied to optical coherence tomography angiography (OCT-A) vascular layers scans from  ...  The combination of preoperative SVP and DVP images showed a significant morphological predictive performance for visual acuity recovery.  ...  Conflicts of Interest: The authors declare no conflict of interest. Diagnostics 2021, 11, 2319  ... 
doi:10.3390/diagnostics11122319 pmid:34943557 pmcid:PMC8700555 fatcat:iair22fyl5fahcjzwxqysdu2p4

Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images

Soichiro Kuwayama, Yuji Ayatsuka, Daisuke Yanagisono, Takaki Uta, Hideaki Usui, Aki Kato, Noriaki Takase, Yuichiro Ogura, Tsutomu Yasukawa
2019 Journal of Ophthalmology  
Although optical coherence tomography (OCT) is essential for ophthalmologists, reading of findings requires expertise.  ...  The purpose of this study is to test deep learning with image augmentation for automated detection of chorioretinal diseases. Methods. A retina specialist diagnosed 1,200 OCT images.  ...  Yasukawa was supported by Grant-in-Aid for Scientific Research (C) 25462758 from the Japan Society for the Promotion of Science.  ... 
doi:10.1155/2019/6319581 pmid:31093370 pmcid:PMC6481014 fatcat:qeyikvecabfc3ese2m724k5apm

The eye, the kidney & cardiovascular disease: old concepts, better tools & new horizons

Tariq E. Farrah, Baljean Dhillon, Pearse A. Keane, David J. Webb, Neeraj Dhaun
2020 Kidney International  
The advent of optical coherence tomography (OCT) has transformed retinal imaging by capturing the chorioretinal microcirculation and its dependent tissue with near-histological resolution.  ...  Combining OCT's deep imaging with the analytical power of deep learning represents the next frontier in defining what the eye can reveal about the kidney and broader cardiovascular health.  ...  .: Retinal imaging and the kidney Figure 4 | 4 Deep imaging with optical coherence tomography (OCT).  ... 
doi:10.1016/j.kint.2020.01.039 pmid:32471642 pmcid:PMC7397518 fatcat:ogno2qf7pvhqdkfkogc7punlki

Predicting Optical Coherence Tomography-Derived High Myopia Grades From Fundus Photographs Using Deep Learning

Zhenquan Wu, Wenjia Cai, Hai Xie, Shida Chen, Yanbing Wang, Baiying Lei, Yingfeng Zheng, Lin Lu
2022 Frontiers in Medicine  
PurposeTo develop an artificial intelligence (AI) system that can predict optical coherence tomography (OCT)-derived high myopia grades based on fundus photographs.MethodsIn this retrospective study, 1,853  ...  We developed a novel deep learning model to detect and predict myopic maculopathy according to the atrophy (A), traction (T), and neovascularisation (N) classification and grading system.  ...  and BL: data analysis and interpretation. YZ, LL, and SC: manuscript revision. All authors wrote the manuscript and approved the final version of the manuscript.  ... 
doi:10.3389/fmed.2022.842680 pmid:35308524 pmcid:PMC8927672 fatcat:so6rqdrgijebbfp6skahctp2ma

Validation and Clinical Applicability of Whole-Volume Automated Segmentation of Optical Coherence Tomography in Retinal Disease Using Deep Learning

Marc Wilson, Reena Chopra, Megan Z. Wilson, Charlotte Cooper, Patricia MacWilliams, Yun Liu, Ellery Wulczyn, Daniela Florea, Cían O. Hughes, Alan Karthikesalingam, Hagar Khalid, Sandra Vermeirsch (+4 others)
2021 JAMA ophthalmology  
Quantitative volumetric measures of retinal disease in optical coherence tomography (OCT) scans are infeasible to perform owing to the time required for manual grading.  ...  To evaluate a deep learning model for whole-volume segmentation of 4 clinically important pathological features and assess clinical applicability.  ...  Segmentations were independently adjudicated by 2 senior ophthalmologists (P.A.K. and K.B.) with Key Points Question Is deep learning-based segmentation of macular disease in optical coherence tomography  ... 
doi:10.1001/jamaophthalmol.2021.2273 pmid:34236406 pmcid:PMC8444027 fatcat:6jbtwbps6zakrgdck5xbrrdmye
« Previous Showing results 1 — 15 out of 1,323 results