|
|
Magnetic resonance imaging via optimization methods
Onderlička, Tomáš ; Šorel,, Michal (referee) ; Rajmic, Pavel (advisor)
Magnetic resonance imaging is a diagnostic method to form images of the organs in the body. Long acquisition times are the main disadvantage, however it is possible to accelerate the data acquisition with the method of compressed sensing by sensing fewer samples and formulating an optimization method for image reconstruction. The aim of this thesis is to describe and compare the common optimization methods and to create a software capable of solving them. Another objective is to observe how much the data acquisition can be accelarated without the loss of image quality when dealing with real data. The most promising method in the experiment was total generalized variation (TGV) regularization which was able to reconstruct an image with a proper quality using only a quarter of the data.
|
|
|
Application of cluster analysis to real data
Onderlička, Tomáš ; Popela, Pavel (referee) ; Žák, Libor (advisor)
This bachelor's thesis deals with finding similar scenarios in the waste management acquired by an optimization tool NERUDA. Cluster analysis, a tool that identifies related objects and classifies them in groups (clusters), is used for this purpose. The aim of this thesis is to review basic algorithms of cluster analysis and to develop a software that implements them. The software is then used to cluster real data from NERUDA which is followed by an assessment of the obtained clusters.
|
|
|
Magnetic resonance imaging via optimization methods
Onderlička, Tomáš ; Šorel,, Michal (referee) ; Rajmic, Pavel (advisor)
Magnetic resonance imaging is a diagnostic method to form images of the organs in the body. Long acquisition times are the main disadvantage, however it is possible to accelerate the data acquisition with the method of compressed sensing by sensing fewer samples and formulating an optimization method for image reconstruction. The aim of this thesis is to describe and compare the common optimization methods and to create a software capable of solving them. Another objective is to observe how much the data acquisition can be accelarated without the loss of image quality when dealing with real data. The most promising method in the experiment was total generalized variation (TGV) regularization which was able to reconstruct an image with a proper quality using only a quarter of the data.
|
|
|
Application of cluster analysis to real data
Onderlička, Tomáš ; Popela, Pavel (referee) ; Žák, Libor (advisor)
This bachelor's thesis deals with finding similar scenarios in the waste management acquired by an optimization tool NERUDA. Cluster analysis, a tool that identifies related objects and classifies them in groups (clusters), is used for this purpose. The aim of this thesis is to review basic algorithms of cluster analysis and to develop a software that implements them. The software is then used to cluster real data from NERUDA which is followed by an assessment of the obtained clusters.
|
guest ::
