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Human Stem Cells for Ophthalmology: Recent Advances in Diagnostic Image Analysis and Computational Modelling
被引:0
作者:
Wadkin, L. E.
[1
]
Makarenko, I.
[1
]
Parker, N. G.
[1
]
Shukurov, A.
[1
]
Figueiredo, F. C.
[2
,3
]
Lako, M.
[3
]
机构:
[1] Newcastle Univ, Sch Math Stat & Phys, Newcastle Upon Tyne, England
[2] Newcastle Tyne Hosp NHS Fdn Trust, Royal Victoria Infirm, Dept Ophthalmol, Newcastle Upon Tyne, England
[3] Newcastle Univ, Biosci Inst, Fac Med Sci, Newcastle Upon Tyne, England
基金:
英国生物技术与生命科学研究理事会;
关键词:
Ophthalmology;
Diagnostic image analysis;
Mathematical modelling;
Human stem cells;
Machine learning;
Agent-based modelling;
STATISTICAL-MECHANICS;
RETINAL ORGANOIDS;
SIMULATION-MODEL;
GENE-THERAPY;
DIFFERENTIATION;
D O I:
10.1007/s40778-023-00229-0
中图分类号:
Q813 [细胞工程];
学科分类号:
摘要:
Purpose of ReviewTo explore the advances and future research directions in image analysis and computational modelling of human stem cells (hSCs) for ophthalmological applications.Recent FindingshSCs 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.SummaryMany 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.
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页码:57 / 66
页数:10
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