|
|
Volumetric Segmentation of Dental CT Data
Berezný, Matej ; Kodym, Oldřich (referee) ; Čadík, Martin (advisor)
The main goal of this work was to use neural networks for volumetric segmentation of dental CBCT data. As a byproducts, both new dataset including sparse and dense annotations and automatic preprocessing pipeline were produced. Additionally, the possibility of applying transfer learning and multi-phase training in order to improve segmentation results was tested. From the various tests that were carried out, conclusion can be drawn that both multi-phase training and transfer learning showed substantial improvement in dice score for both sparse and dense annotations compared to the baseline method.
|
|
|
Deep Learning for Medical Image Analysis
Osvald, Martin ; Juránek, Roman (referee) ; Španěl, Michal (advisor)
The goal of this bachelor's thesis is to use the 2D convolutional neural network on the 3D model dataset by multi-view methods. The view is 2D picture of 3D model. The result are Pyqt applications, where is possible to load the 3D model of teeth and predict the location of landmarks and teeth by object segmentation and object detection. During this thesis, an annotation's script was created for the annotation of 3D models for landmarks of teeth and teeth themself. This thesis solves the problem of the small availability of annotated 3D datasets in the medical industry by automating generating binary masks from different views on 3D models.
|
|
|
Rendering Volumetric Data in Web Browser
Fisla, Jakub ; Zemčík, Pavel (referee) ; Španěl, Michal (advisor)
This thesis discusses rendering capabilities of web browsers of accelerated 3D scene rendering. It specifically deals with direct volumetric medical data visualization. It focuses on the usage of ray casting algorithm, its quality and its realistic rendering options. One of the goals was to create an application that demonstrates the ability to render three-dimensional volume data in a web browser using WebGL. The application is written in JavaSript and its 3D rendering core uses the Three.js library.
|
|
|
Deep Learning for Medical Image Analysis
Osvald, Martin ; Juránek, Roman (referee) ; Španěl, Michal (advisor)
The goal of this bachelor's thesis is to use the 2D convolutional neural network on the 3D model dataset by multi-view methods. The view is 2D picture of 3D model. The result are Pyqt applications, where is possible to load the 3D model of teeth and predict the location of landmarks and teeth by object segmentation and object detection. During this thesis, an annotation's script was created for the annotation of 3D models for landmarks of teeth and teeth themself. This thesis solves the problem of the small availability of annotated 3D datasets in the medical industry by automating generating binary masks from different views on 3D models.
|
|
|
Volumetric Segmentation of Dental CT Data
Berezný, Matej ; Kodym, Oldřich (referee) ; Čadík, Martin (advisor)
The main goal of this work was to use neural networks for volumetric segmentation of dental CBCT data. As a byproducts, both new dataset including sparse and dense annotations and automatic preprocessing pipeline were produced. Additionally, the possibility of applying transfer learning and multi-phase training in order to improve segmentation results was tested. From the various tests that were carried out, conclusion can be drawn that both multi-phase training and transfer learning showed substantial improvement in dice score for both sparse and dense annotations compared to the baseline method.
|
|
|
Rendering Volumetric Data in Web Browser
Fisla, Jakub ; Zemčík, Pavel (referee) ; Španěl, Michal (advisor)
This thesis discusses rendering capabilities of web browsers of accelerated 3D scene rendering. It specifically deals with direct volumetric medical data visualization. It focuses on the usage of ray casting algorithm, its quality and its realistic rendering options. One of the goals was to create an application that demonstrates the ability to render three-dimensional volume data in a web browser using WebGL. The application is written in JavaSript and its 3D rendering core uses the Three.js library.
|
guest ::
