Přehled

Title: Computational Analysis of Retinal Microvasculature and Photoreceptors

Study program: Biomedical Technology and Bioinformatics

Supervisor: Doc. Ing. Radim Kolář, Ph.D.

Topic description:

Over the past decade, rapid advances in retinal imaging – particularly through adaptive optics (AO) – have brought a significant shift in the ability to achieve resolution down to the level of individual cells. This technological revolution enables in vivo study of previously unexplored microscopic structures of the retina, while at the same time creating the need for entirely new methods for processing such data.

This PhD project focuses on a detailed analysis of retinal vasculature and the photoreceptor layer using modern algorithms, including advanced segmentation and detection of pathological changes, multimodal image registration from various sources, and automated image quality assessment and artefact suppression. The research will involve the use of deep learning for precise segmentation and classification of structures, the development of explainable AI for improved interpretation of results in clinical practice, the design of methodologies for longitudinal tracking of retinal microstructures to predict disease progression, and the application of multimodal imaging data in personalised medicine.

The project offers opportunities to engage in ongoing research conducted in collaboration with the University of Leipzig, specifically in the areas of studying the effects of pregnancy on the ocular vascular system, evaluating the impact of new pharmacological therapies on retinal microstructure, and integrating data from multidimensional.

Your tasks:

  • Develop advanced image processing and machine learning methods for high-resolution retinal imaging – segmentation, classification, multimodal image registration of retinal data.

  • Conduct longitudinal analysis to track retinal changes and support early disease detection.

  • Develop interpretable AI methods in collaboration with clinicians.

  • Integrate imaging data with clinical and functional parameters.

  • Scientific publishing in peer-reviewed international journals and at conferences.

Requirements:

  • Master’s degree in a relevant field such as computer science or biomedical engineering.

  • Programming skills (preferably in Python, MATLAB, or C++) and experience with machine learning algorithms.

  • Good communication skills in English,

  • Strong interest or experiences in ophthalmic research is an advantage.

We offer:

  • Work in an active team with opportunities for collaboration with a range of experts.

  • Friendly and supportive research environment.

  • Professional development through participation in international conferences, workshops as well as student’s mentorship and teaching.

Relevant publications:

https://doi.org/10.1364/BOE.471881

https://doi.org/10.1016/j.preghy.2023.12.004

https://doi.org/10.1364/BOE.486052

For more information about this topic please contact Radim Kolář – kolarr@vut.cz.

Application portal: https://www.vut.cz/eprihlaska/

Application deadline: April 30, 2026

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