|
|
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.
|
|
|
Automatic speech recordings segmentation tool
Santa, Roman ; Zvončák, Vojtěch (referee) ; Kováč, Daniel (advisor)
Nástroj pre automatickú segmentáciu spracováva nahrávky reči a extrahuje hovorené slovo z nahrávok. Je dôležité, aby pokročilá analýza pracovala iba s rečovými časťami z nahrávky. Nástroj na segmentáciu má ulahčiť spracovanie nahrávok pre analýzu rozdielov medzi hláskami pacientov s parkinsonovou chorobou a tými zdravými. Cieľ tejto práce je navrhnúť a otestovať detektory reči s Google WebRTC detektorom a vybrať ten najvhodnejší detektor reči s minimálnym počtom chýb. Ďalej, vytvoriť nástroj na segmentáciu nahrávok a otestovať rozpoznávanie reči pomocou dynamic time warping. Bola použitá databáza poskytnutá laboratóriom pre analýzu mozgových ochorení. Obsahuje české a maďarské nahrávky s rovnakým počtom mužských a ženských pacientov a aj rovnakým počtom zdravých pacientov a pacientov s parkinsonovou chorobou. Najlepšie výsledky v testoch dosiahol detektor na základe energie reči. Nebol zistený žiaden rozdiel v presnosti detektoru pri spracovaní mužských a ženských nahrávok alebo nahrávok zdravých či chorých pacientov. Nahrávky s nízkym odstupom signálu od šumu boli náročnejšie na spracovanie s frekvenciou chýb od 12%. Na základe výsledkov, bol navrhnutý nový detektor pre spracovanie úplnej nahrávky. Na záver bol testovaný algoritmus pre rozpoznávanie podobnosti reči na základe melovských kepstrálnych koeficientov.
|
|
|
Analysis of neurite directionality
Plišková, Diana ; Čmiel, Vratislav (referee) ; Odstrčilík, Jan (advisor)
Práca je zameraná na navrhnutie vhodnej metódy analýzy smerovosti neuritov. Využité boli snímky neurónov z fluorescenčnej mikroskopie. Pred samotnou segmentáciou bolo potrebné snímky predspracovať, pričom sa postupne využila úprava kontrastu, ostrenie a adaptívna filtrácia pomocou Weinerovského filtru. Jednotlivé návrhy metód segmentácie pozostávali z prostého prahovania, narastaním oblastí a využitím morfologických operácií. Následná analýza smerovosti využívala smer gradientov v obraze. Navrhnutá metóda bola využitá aj ako klasifikátor, ktorý dokázal rozdeliť jednotlivé snímky do skupín podľa smeru rastu.
|
|
|
Object Detection in the Laser Scans Using Convolutional Neural Networks
Zelenák, Michal ; Kodym, Oldřich (referee) ; Veľas, Martin (advisor)
This work is focused on road segmentation in laser scans, using a convolutional neural network. To achieve this goal, which will find application in the field of road maintenance, convolutional neural networks have been used for their flexibility and speed. The work brings implementation and modifications of the existing method, which solves the problem by using a fully connected convolutional neural network. Used modifications include, for example using of various parameters for the loss function, the use of a different number of classes in the network model and dataset. The effect of the modification was experimentally verified and the accuracy of 96.12%, and the value for F-measure 95.02% were achieved.
|
|
|
Polygonal Mesh Segmentation
Švancár, Matúš ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
This bachelor thesis analyzes and approaches the issue of segmentation of polygonal models. It presents a design of an interactive method inspired by the method described in the Interactive Mesh Segmentation Based on Feature Preserving Harmonic Field. The method uses graph-cut and is implemented as a web application. The application supports .obj and .stl file formats, allows the user to load a model, draw sketches representing foreground and background on the surface of the model, and to start segmentation. Once completed, the user can download the resulting models or continue segmenting with one of them.
|
|
|
Segmentation of cardiac tissue fibrosis in MRI data
Sokol, Norbert ; Mézl, Martin (referee) ; Kolář, Radim (advisor)
Late gadolinium enhancement cardiovascular magnetic resonance imaging can be used to visualize pre-ablation fibrosis or post-ablation myocardial scar. This can significantly helps physicians with diagnosis patients who suffer from myocardial fibrosis to determine region of fibrosis and for post-operative validation of intervention after radio-frequency catheter ablation. In this thesis, i introduce an algorithm for successful distinguish of fibrosis on datasets of patients with myocardial fibrosis, scanned at Faculty hospital at St. Anne’s University Hospital.
|
|
|
Segmentation of the cord canal and intervertebral discs in MRI data
Koban, Martin ; Odstrčilík, Jan (referee) ; Jakubíček, Roman (advisor)
The concern of this thesis is development of the method for the spinal canal and intervertebral discs segmentation in volume MRI data. The primary aim is to achieve the highest possible level of automation and accuracy allowing for reliable quantitative evaluation of the results. The algorithm is based on the random walk model in combination with a specific active contour method formulated through level set concept. The proposed approach is tested using a database of three-dimensional T2-weighted MR images, which also contains referential manual segmentation of intervertebral discs.
|
|
|
Segmentation of cardiac tissue fibrosis in MRI data
Sokol, Norbert ; Mézl, Martin (referee) ; Kolář, Radim (advisor)
Late gadolinium enhancement cardiovascular magnetic resonance imaging can be used to visualize pre-ablation fibrosis or post-ablation myocardial scar. This can significantly helps patients with myocardial fibrosis to determine region of fibrosis and for post-operative validation of intervention after radio-frequency catheter ablation. In this thesis, i introduce an algorithm for successful distinguish of fibrosis on datasets of patients with myocardial fibrosis, scanned at Faculty hospital at St. Anne’s University Hospital.
|
|
|
Automatic classification of pronunciation of the letter „R“
Hrušovský, Enrik ; Vičar, Tomáš (referee) ; Harabiš, Vratislav (advisor)
This diploma thesis deals with automatic clasification of vowel R. Purpose of this thesis is to made program for detection of pronounciation of speech defects at vowel R in children. In thesis are processed parts as speech creation, speech therapy, dyslalia and subsequently speech signal processing and analysis methods. In the last part is designed software for automatic detection of pronounciation of vowel R. For recognition of pronounciation is used algorithm MFCC for extracting features. This features are subsequently classified by neural network to the group of correct or incorrect pronounciation and is evaluated classification success.
|
|
|
Czech startups from a gender perspective
Irikovská, Alexandra ; Nyklová, Blanka (advisor) ; Pospíšilová, Marie (referee)
This thesis attempts to answer the question why there are so few female founders of startup companies in the Czech Republic. In order to identify the main roots of gender inequality in this field and obtain a detailed understanding of the gender culture of Czech startups, biographic-narrative interviews were conducted with women in managing positions as well as female founders of Czech startups. Through in-depth analysis of these women's narratives, key areas were identified which contribute to the reproduction of gender segregation in this field. The research found that the inequality is mainly caused by gender stereotypes towards women in the field of technology, which even the interviewed women reproduce through identification with a specific type of masculinity. In an attempt to fulfill the gendered expectations from an ideal startup founder or manager women often find themselves in conflict with the traditional role of women in the Czech Republic. The second group of women on the other hand emphasize the importance of femininity and indentify themselves against this type of masculinity. The analysis also showed the importance of the gender inequalities in the technical field of education, that are also reflected in the startups. The author recommends a further research into the following areas...
|
guest ::
