Purpose of review: To explore the advances and future research directions in image analysis and computational modelling of human stem cells (hSCs) for ophthalmological applications.
Recent findings: hSCs hold great potential in ocular regenerative medicine due to their application in cell-based therapies and in disease modelling and drug discovery using state-of-the-art 2D and 3D organoid models. However, a deeper characterisation of their complex, multi-scale properties is required to optimise their translation to clinical practice. Image analysis combined with computational modelling is a powerful tool to explore mechanisms of hSC behaviour and aid clinical diagnosis and therapy.
Summary: Many computational models draw on a variety of techniques, often blending continuum and discrete approaches, and have been used to describe cell differentiation and self-organisation. Machine learning tools are having a significant impact in model development and improving image classification processes for clinical diagnosis and treatment and will be the focus of much future research.
Keywords: Agent-based modelling; Diagnostic image analysis; Human stem cells; Machine learning; Mathematical modelling; Ophthalmology.
© The Author(s) 2023.