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Measurement and processing of diffusion data from magnetic resonance
Vankó, Bence ; Jiřík, Radovan (referee) ; Kolářová, Jana (advisor)
This bachelor thesis deals with DTI examination. The diffusion tensor model of magnetic resonance imaging is a modern diagnostic method mainly used to visualize the spatial relationship of a particular neuronal pathway of the brain. The work is divided into three main parts. The first part contains the theoretical introduction to MRI, DTI and literary research from individual scientific articles dealing with DTI experiments. The second part of the thesis deals with the search of electronic articles to choose the right acquisition. Based on the articles being studied, parameters were selected and polished during the measuring of the phantom. In the third part, the measurements are done on the basis of the resulting acquisition protocol and the data is processed in various software.
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Tracking of axonal bundles in diffusion MRI brain images
Piskořová, Zuzana ; Vojtíšek, Lubomír (referee) ; Labounek, René (advisor)
The aim of this thesis is to design tracking algorithm which will be able to track white matter bundles in diffusion MRI data, this problem is called tractography. Tractography is feasible because specific profile of diffusion appears in white matter. The introduction to the topic includes summary of methods for estimation of diffusion profile and basic tracking algorithms. In this work diffusion tensor model (DTI) was used for estimation of diffusion profile. Based on the DTI, vector field characterizing direction of diffusion for every voxel was created. Combining vector field with seedpoint, we achieved task solvable by Euler or Runge-Kutta method. Termination criteria were established for maximum curvature of trajectory and minimum value of fractional anisotropy (FA). Algorithm was tested on mathematical and tractographical phantom before it was used on real biological data. The results of tracking on phantoms proved the funcionality of the algorithm. Expected error appeared in areas of crossing fibers, it is related to DTI model limitations. To solve problematic fibers characterized by seedpoint near the border of the fiber, FA-weighted trilinear interpolation was designed. Implementation of this algorithm, however, did not cause better results. The results of tracking on the real data were controversial. Tracking was performed on 5 healthy subjects and 4 anatomicaly specific tracts. The results were compared with tractographic atlas.
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Measurement and processing of diffusion data from magnetic resonance
Vankó, Bence ; Jiřík, Radovan (referee) ; Kolářová, Jana (advisor)
This bachelor thesis deals with DTI examination. The diffusion tensor model of magnetic resonance imaging is a modern diagnostic method mainly used to visualize the spatial relationship of a particular neuronal pathway of the brain. The work is divided into three main parts. The first part contains the theoretical introduction to MRI, DTI and literary research from individual scientific articles dealing with DTI experiments. The second part of the thesis deals with the search of electronic articles to choose the right acquisition. Based on the articles being studied, parameters were selected and polished during the measuring of the phantom. In the third part, the measurements are done on the basis of the resulting acquisition protocol and the data is processed in various software.
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Tracking of axonal bundles in diffusion MRI brain images
Piskořová, Zuzana ; Vojtíšek, Lubomír (referee) ; Labounek, René (advisor)
The aim of this thesis is to design tracking algorithm which will be able to track white matter bundles in diffusion MRI data, this problem is called tractography. Tractography is feasible because specific profile of diffusion appears in white matter. The introduction to the topic includes summary of methods for estimation of diffusion profile and basic tracking algorithms. In this work diffusion tensor model (DTI) was used for estimation of diffusion profile. Based on the DTI, vector field characterizing direction of diffusion for every voxel was created. Combining vector field with seedpoint, we achieved task solvable by Euler or Runge-Kutta method. Termination criteria were established for maximum curvature of trajectory and minimum value of fractional anisotropy (FA). Algorithm was tested on mathematical and tractographical phantom before it was used on real biological data. The results of tracking on phantoms proved the funcionality of the algorithm. Expected error appeared in areas of crossing fibers, it is related to DTI model limitations. To solve problematic fibers characterized by seedpoint near the border of the fiber, FA-weighted trilinear interpolation was designed. Implementation of this algorithm, however, did not cause better results. The results of tracking on the real data were controversial. Tracking was performed on 5 healthy subjects and 4 anatomicaly specific tracts. The results were compared with tractographic atlas.
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