Shashank Bhandary | Azam Darvishi | Samaneh Hashemi | Asif Iqbal | Mahdi Heravian Shandiz | Jason Kugelman | Yoel Garcia Marin | Ignacio Escalona Viedma
Shashank Bhandary
Thesis Title: Using objective methods to understand the effects of near activities on myopia-genic visual environment factors
Shashank arrived in Brisbane, in July 2023, ready to commence full-time higher degree research studies within QUT’s Optometry and Vision research discipline. Shashank’s research project will utilise novel objective measurement methods to investigate visual environment factors associated with myopia. This will provide new insights into the impact of the modern visual environment and visual tasks upon myopia, and potentially identify novel treatment methods and strategies for preventing myopia development. Shashank’s thesis is guided by principal supervisor, Professor Scott Read, and Associate Supervisors: Aspro. Stephen Vincent and Prof. Michael Collins.
Azam Darvishi
Thesis Title: Investigation of the effects of different wavelengths of light on myopia
Azam commenced her PhD candidature in June 2023. Azam’s Principal Supervisor is Professor Scott Read, with supervisory support being provided by Associate Professor Stephen Vincent.
Azam’s research project will investigate the effects of different wavelengths of light, on myopia. Despite the relationship between light intensity and myopia, the effects of various light wavelengths and their effects upon myopia have gained momentum and interest. Refractive growth is influenced by the ambient spectral composition. The purpose of Azam’s research study is to determine the effects of short-wavelength lighting and long-wavelength lighting on choroidal thickness in humans.
Samaneh Hashemi
Thesis Title: Ocular/Tissue blood flow imaging using optical coherence tomography angiography
Samaneh commenced her PhD journey as a full-time QUT student in May 2023. Her research project will focus on the optical coherence tomography angiography (OCT-A) images of the human eye with an emphasis on quantifying image processing and overcoming specific OCT-A’s imaging limitations in the posterior area of the eye. Samaneh’s QUT HDR Principal Supervisor is Professor Zhiyong Li (School of Mech. Med. & Proc. Eng.), with supervisory support provided by Centre for Vision & Eye Research staff: Dr David Alonso Caneiro, Professor Scott Read and Professor Michael Collins.
Asif Iqbal
Thesis Title: Tear exchange during scleral lens wear and its association with central and peripheral corneal oedema with different lens fitting characteristics
Asif Iqbal commenced his PhD candidature in the Contact Lens and Visual Optics Laboratory at QUT’s School of Optometry and Vision Science, in October 2022. Asif’s Principal Supervisor is Associate Professor and Academic Lead, Stephen Vincent, and his Associate Supervisors are Professor Michael Collins, Dr Damien Fisher and Dr David Alonso-Caneiro.
Asif’s research project aims to quantify tear exchange during scleral lens wear, with a focus on the occurrence of central and peripheral corneal oedema when scleral lenses with differing lens fitting characteristics are introduced. Asif also plans to investigate how varying lens modification options may improve tear exchange and ensue a positive impact on corneal physiology.
Publications (arising from thesis):
Iqbal, Asif, Fisher, Damien, Alonso Caneiro, David, Collins, Michael, & Vincent, Steve (2023) Central and peripheral scleral lens-induced corneal oedema. Ophthalmic and Physiological Optics.
Mahdi Heravian Shandiz
Thesis Title: Towards a more efficient platform for analysing retinal images via machine learning
Mahdi commenced his PhD candidature as a part-time external student in May 2021. Mahdi’s Principal Supervisor is Dr David Alonso-Caneiro, with Associate Supervisors, Professor Michael Collins and Associate Professor Scott Read. His research project will investigate the use of machine learning methods for the analysis and quantification of medical images of the human eye, with a particular focus on the posterior segment of the eye.
Jason Kugelman
Thesis Title: Application of generative deep learning models in ophthalmic imaging
Jason begins his PhD candidature at QUT in January 2021. His research project will investigate generative deep learning methods such as generative adversarial networks (GANs), and their application to ophthalmic images as well as the potential extensibility of new and modified techniques beyond this domain. Applications include data augmentation, super resolution, de-noising + de-artifacting, domain translation, image segmentation and anomaly detection, among others. The aim is to use these methods to improve image analysis in ophthalmology, supporting research, clinical practice and diagnostics, while the potential of applying new methods beyond this domain is likely to have general positive benefits in the area of deep learning-based image analysis.
Publications (arising from thesis):
Charng, Jason, Alam, Khyber, Swartz, Gavin, Kugelman, Jason, Alonso-Caneiro, David, Mackey, David A., et al. (2023) Deep learning: applications in retinal and optic nerve diseases. Clinical and Experimental Optometry, 106(5), pp. 466-475.
Kugelman, Jason, Alonso-Caneiro, David, Read, Scott A., & Collins, Michael J. (2022) A review of generative adversarial network applications in optical coherence tomography image analysis. Journal of Optometry, 15, S1-S11.
Yoel Garcia Marin
Thesis Title: Deep learning methods applied to anterior eye optical coherence tomography images
Yoel’s research project is focused on the development of effective and automatic deep learning algorithms to be applied in anterior segment optical coherence tomography (AS-OCT) images. This covers a range of tasks including segmentation, classification and image quality assessment/improvement.
Since currently there are only a limited number of studies that have addressed the use of deep learning methods in anterior segment images, the procedures that will be developed represent a novel and innovative solution to current problems found in AS-OCT image analysis. Given the potential that deep learning methods have demonstrated in a number of imaging modalities, including the in posterior segment OCT images, this thesis aims to create effective and powerful methods that can be applied to both clinical and research applications.
Publications (arising from thesis):
Garcia-Marin, Yoel F., Alonso-Caneiro, David, Fisher, Damien, Vincent, Stephen J., & Collins, Michael J. (2023) Patch-based CNN for corneal segmentation of AS-OCT images: Effect of the number of classes and image quality upon performance. Computers in Biology and Medicine, 152, Article number: 106342.
Garcia Marin, Francisco Yoel, Alonso Caneiro, David, Vincent, Stephen, & Collins, Michael (2022) Anterior segment optical coherence tomography (AS-OCT) image analysis methods and applications: A systematic review. Computers in Biology and Medicine, 146, Article number: 105471.
Garcia Marin, Yoel, Skrok, Marta, Siedlecki, Damian, Vincent, Stephen J., Collins, Michael J., & Alonso-Caneiro, David (2021) Segmentation of anterior segment boundaries in swept source OCT images. Biocybernetics and Biomedical Engineering, 41(3), pp. 903-915.
Ignacio Escalona Viedma
Thesis Title: Automatic layer segmentation in retinal OCT imaging using deep learning methods
Ignacio’s research program involves the development of image analysis methods for Optical Coherence Tomography (OCT) images of the posterior segment of the eye (retina). He aims to develop accurate methods of segmentation using supervised and unsupervised Deep Learning approaches as well as pre-processing task that can support the segmentation task. The developed tools will provide automatic segmentation methods that can be used in a range of clinical and research studies. He is interested in exploring novel methods that have not been used for such an application, as well as the development of techniques that can be used in a range of different instruments (instrument-independent image analysis methods).
Publications (arising from thesis):
Viedma, Ignacio A., Alonso-Caneiro, David, Read, Scott A., & Collins, Michael J. (2022) Deep learning in retinal optical coherence tomography (OCT): A comprehensive survey. Neurocomputing, 507, pp. 247-264.
Viedma Escalona, Ignacio Andres, Alonso Caneiro, David, Read, Scott, & Collins, Michael (2022) OCT Retinal and Choroidal Layer Instance Segmentation Using Mask R-CNN. Sensors (Switzerland), 22(5), Article number: 2016.
Viedma Escalona, Ignacio Andres, Alonso-Caneiro, David, Read, Scott, & Collins, Michael (2021) OCT retinal image-to-image translation: Analysing the use of CycleGAN to improve retinal boundary semantic segmentation. In Zhou, Jun, Salvado, Olivier, Sohel, Ferdous, Borges, Paulo Vinicius K., & Wang, Shilin (Eds.) Proceedings of the 2021 Digital Image Computing: Techniques and Applications (DICTA). Institute of Electrical and Electronics Engineers Inc., United States of America.