Scott A. Read

Orcid: 0000-0002-1595-673X

Affiliations:

Queensland University of Technology, Brisbane, Australia

According to our database¹, Scott A. Read authored at least 11 papers between 2018 and 2023.

Collaborative distances:

Dijkstra number² of six.
Erdős number³ of five.

Timeline

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PhD thesis

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Bibliography

2023

Enhanced OCT chorio-retinal segmentation in low-data settings with semi-supervised GAN augmentation using cross-localisation.

[BibT_eX]

[DOI]

Comput. Vis. Image Underst., December, 2023

2022

OCT Retinal and Choroidal Layer Instance Segmentation Using Mask R-CNN.

[BibT_eX]

[DOI]

Sensors, 2022

Deep learning in retinal optical coherence tomography (OCT): A comprehensive survey.

[BibT_eX]

[DOI]

Neurocomputing, 2022

2021

Data augmentation for patch-based OCT chorio-retinal segmentation using generative adversarial networks.

[BibT_eX]

[DOI]

Neural Comput. Appl., 2021

OCT retinal image-to-image translation: Analysing the use of CycleGAN to improve retinal boundary semantic segmentation.

[BibT_eX]

[DOI]

Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021

OCT chorio-retinal segmentation with adversarial loss.

[BibT_eX]

[DOI]

Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021

Use of uncertainty quantification as a surrogate for layer segmentation error in Stargardt disease retinal OCT images.

[BibT_eX]

[DOI]

Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021

2020

Effect of Altered OCT Image Quality on Deep Learning Boundary Segmentation.

[BibT_eX]

[DOI]

IEEE Access, 2020

Dual image and mask synthesis with GANs for semantic segmentation in optical coherence tomography.

[BibT_eX]

[DOI]

Proceedings of the Digital Image Computing: Techniques and Applications, 2020

2019

Constructing Synthetic Chorio-Retinal Patches using Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 2019 Digital Image Computing: Techniques and Applications, 2019

2018

Automatic Retinal and Choroidal Boundary Segmentation in OCT Images Using Patch-Based Supervised Machine Learning Methods.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ACCV 2018 Workshops, 2018

Scott A. Read

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