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Automated analysis of retinal imaging using machine learning techniques for computer vision.

J. Fauw, P. Keane, N. Tomasev, D. Visentin, G. van den Driessche, M. Johnson, C. Hughes, C. Chu, J. Ledsam, T. Back, T. Peto, G. Rees, H. Montgomery, R. Raine, O. Ronneberger, and J. Cornebise. F1000Research, (2016)

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Michael Keane

R. A. A. Bowler

Â°Ake Â°Akerström

Mohamed A A Anndif

Eltohamy A A Yousef

Other publications of authors with the same name

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning.A. Varadarajan, P. Bavishi, P. Raumviboonsuk, P. Chotcomwongse, S. Venugopalan, A. Narayanaswamy, J. Cuadros, K. Kanai, G. Bresnick, M. Tadarati and 8 other author(s). CoRR, (2018)With an eye to AI and autonomous diagnosis.P. Keane, and E. Topol. npj Digit. Medicine, (2018)A Linear Approach to Absolute Pose Estimation for Light Fields.S. Nousias, M. Lourakis, P. Keane, S. Ourselin, and C. Bergeles. 3DV, page 672-681. IEEE, (2020)Learning to Address Intra-segment Misclassification in Retinal Imaging.Y. Zhou, M. Xu, Y. Hu, H. Lin, J. Jacob, P. Keane, and D. Alexander. MICCAI (1), volume 12901 of Lecture Notes in Computer Science, page 482-492. Springer, (2021)Deep learning for predicting refractive error from retinal fundus images.A. Varadarajan, R. Poplin, K. Blumer, C. Angermüller, J. Ledsam, R. Chopra, P. Keane, G. Corrado, L. Peng, and D. Webster. CoRR, (2017)A Hybrid Machine Learning Approach Using LBP Descriptor and PCA for Age-Related Macular Degeneration Classification in OCTA Images.A. Alfahaid, T. Morris, T. Cootes, P. Keane, H. Khalid, N. Pontikos, P. Sergouniotis, and K. Balaskas. MIUA, volume 1065 of Communications in Computer and Information Science, page 231-241. Springer, (2019)Code-free deep learning for multi-modality medical image classification.E. Korot, Z. Guan, D. Ferraz, S. Wagner, G. Zhang, X. Liu, L. Faes, N. Pontikos, S. Finlayson, H. Khalid and 4 other author(s). Nat. Mach. Intell., 3 (4): 288-298 (2021)VAFO-Loss: VAscular Feature Optimised Loss Function for Retinal Artery/Vein Segmentation.Y. Zhou, M. Xu, Y. Hu, S. Blumberg, A. Zhao, S. Wagner, P. Keane, and D. Alexander. CoRR, (2022)Automated analysis of retinal imaging using machine learning techniques for computer vision.J. Fauw, P. Keane, N. Tomasev, D. Visentin, G. van den Driessche, M. Johnson, C. Hughes, C. Chu, J. Ledsam, T. Back and 6 other author(s). F1000Research, (2016)"Yes, but will it work for my patients?" Driving clinically relevant research with benchmark datasets.T. Panch, T. Pollard, H. Mattie, E. Lindemer, P. Keane, and L. Celi. npj Digit. Medicine, (2020)

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Disambiguation of "Keane, Pearse A."

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Automated analysis of retinal imaging using machine learning techniques for computer vision.

Please choose a person to relate this publication to

Michael Keane

R. A. A. Bowler

Â°Ake Â°Akerström

Mohamed A A Anndif

Eltohamy A A Yousef

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Keane, Pearse A."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Automated analysis of retinal imaging using machine learning techniques for computer vision.

Please choose a person to relate this publication to

Michael Keane

R. A. A. Bowler

Â°Ake Â°Akerström

Mohamed A A Anndif

Eltohamy A A Yousef

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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MSOffice XML

Automated analysis of retinal imaging using machine learning techniques for computer vision.