Processing biomedical images for the study of treatments related to neurodegenerative diseases
The study of neuronal cell morphology and function in neurodegenerative disease processes is essential in order to develop suitable treatments. In fact, studies such as the quantification of either synapses or the neuronal density are instrumental in measuring the evolution and the behaviour of neur...
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| Formato: | text (thesis) |
| Lenguaje: | eng |
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Universidad de La Rioja (España)
2017
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| Acceso en línea: | https://dialnet.unirioja.es/servlet/oaites?codigo=122711 |
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| Sumario: | The study of neuronal cell morphology and function in neurodegenerative disease processes is essential in order to develop suitable treatments.
In fact, studies such as the quantification of either synapses or the neuronal density are instrumental in measuring the evolution and the behaviour of neurons under the effects of certain physiological conditions.
In order to analyse this data, fully automatic methods are required. To this end, we have studied and developed methods inspired by Computational Algebraic Topology and Machine Learning techniques. Notions such as the definition of connected components, or others related to the persistence homology and zigzag persistence theory have been used to compute the synaptic density or to recognise the neuronal structure. In addition, machine learning methods are used to determine where neurons are located in large images and to ascertain which are the best features to describe this kind of cells. |
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