Tear film breakup time-based dry eye disease detection using convolutional neural network

[1]  Anis Yazidi,et al.  Artificial Intelligence in Dry Eye Disease , 2021, medRxiv.

[2]  J. Wolffsohn,et al.  Patient-reported experience of dry eye management: An international multicentre survey. , 2021, Contact lens & anterior eye : the journal of the British Contact Lens Association.

[3]  K. Tsubota,et al.  Smart Eye Camera: A Validation Study for Evaluating the Tear Film Breakup Time in Human Subjects , 2021, Translational vision science & technology.

[4]  V. Vitelli,et al.  Tear Film Break-Up Time and Dry Eye Disease Severity in a Large Norwegian Cohort , 2021, Journal of clinical medicine.

[5]  L. Schmetterer,et al.  Novel Approaches for Imaging-Based Diagnosis of Ocular Surface Disease , 2020, Diagnostics.

[6]  J. Mehta,et al.  Objective Imaging Diagnostics for Dry Eye Disease , 2020, Journal of ophthalmology.

[7]  Joel Koh En Wei,et al.  Thoughts concerning the application of thermogram images for automated diagnosis of dry eye – A review , 2020 .

[8]  Shaojie Tang,et al.  A survey on incorporating domain knowledge into deep learning for medical image analysis , 2020, Medical Image Anal..

[9]  Praveen Kumar Reddy Maddikunta,et al.  Deep neural networks to predict diabetic retinopathy , 2020, Journal of Ambient Intelligence and Humanized Computing.

[10]  Praveen Kumar Reddy Maddikunta,et al.  Early Detection of Diabetic Retinopathy Using PCA-Firefly Based Deep Learning Model , 2020, Electronics.

[11]  J. Craig,et al.  Epidemiologic Research in Dry Eye Disease and the Utility of Mobile Health Technology. , 2019, JAMA ophthalmology.

[12]  H. Snieder,et al.  The relationship between occupation and dry eye. , 2019, The ocular surface.

[13]  A. Galor.  Painful Dry Eye Symptoms: A Nerve Problem or a Tear Problem? , 2019, Ophthalmology.

[14]  Beatriz Remeseiro,et al.  iDEAS: A web-based system for dry eye assessment , 2016, Comput. Methods Programs Biomed..

[15]  Noelia Barreira,et al.  Computational approach for tear film assessment based on break-up dynamics , 2015 .

[16]  Chua Kuang Chua,et al.  Automated diagnosis of dry eye using infrared thermography images , 2015 .

[17]  Hui Lin,et al.  Dry eye disease: A review of diagnostic approaches and treatments. , 2014, Saudi journal of ophthalmology : official journal of the Saudi Ophthalmological Society.

[18]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[19]  Manuel G. Penedo,et al.  Automation of the tear film break-up time test , 2011, ISABEL '11.

[20]  M. Helvaci,et al.  Ocular Surface Disease Index for the Diagnosis of Dry Eye Syndrome , 2007, Ocular immunology and inflammation.

[21]  A. Bron,et al.  Grading Of Corneal and Conjunctival Staining in the Context of Other Dry Eye Tests , 2003, Cornea.

[22]  I H Leopold,et al.  Interpretation of tear film breakup. , 1977, Archives of ophthalmology.

[23]  Aditi Vyas,et al.  A Comprehensive Survey on Image Modality based Computerized Dry Eye Disease Detection Techniques , 2020 .

[24]  K. Tsubota,et al.  New Perspectives on Dry Eye Definition and Diagnosis: A Consensus Report by the Asia Dry Eye Society. , 2017, The ocular surface.

[25]  R. Joe Stanley,et al.  Medical Image Processing in the Age of Deep Learning - Is There Still Room for Conventional Medical Image Processing Techniques? , 2017, VISIGRAPP.