Thesis etd-05302011-155516 |
Link copiato negli appunti
Thesis type
Tesi di laurea specialistica
Author
SALVETTI, FEDERICA
URN
etd-05302011-155516
Thesis title
Design and comparison of Hidden Markov Models for pattern recognition of cerebral White Matter Lesions on MRI.
Department
INGEGNERIA
Course of study
INGEGNERIA DELLE TELECOMUNICAZIONI
Supervisors
relatore Corsini, Giovanni
relatore Pham, Tuan
relatore Prof. Diani, Marco
relatore Pham, Tuan
relatore Prof. Diani, Marco
Keywords
- Hidden Markov Model
- MRI
- pattern recognition
- White Matter Lesions
Graduation session start date
27/06/2011
Availability
Partial
Release date
27/06/2051
Summary
The research conducted in the present thesis proposes a computational neuroscience framework aiming to analyze the similarity/dissimilarity of white matter lesions (WML) patterns on FLAIR MRI, where WMLs appear hyperintense.
The study uses the concepts of Hidden Markov Model, fractals and phylogeny, which is used to discover the pattern of relationships of organisms.
The outcome of the proposed stochastic model is a tree where patients are grouped based on the relationship of their WMH patterns in term of size, shape and spatial distribution.
The study uses the concepts of Hidden Markov Model, fractals and phylogeny, which is used to discover the pattern of relationships of organisms.
The outcome of the proposed stochastic model is a tree where patients are grouped based on the relationship of their WMH patterns in term of size, shape and spatial distribution.
File
| Nome file | Dimensione |
|---|---|
| Conclusions.pdf | 35.03 Kb |
| index.pdf | 14.00 Kb |
| Introduction.pdf | 274.28 Kb |
5 file non consultabili su richiesta dell’autore. |
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