National Repository of Grey Literature 16 records found  1 - 10next  jump to record: Search took 0.01 seconds. 
Intracranial hemorrhage localization in axial slices of head CT images
Kopečný, Kryštof ; Chmelík, Jiří (referee) ; Nemček, Jakub (advisor)
This thesis is focused on detection of intracranial hemorrhage in CT images using both one-stage and two-stage object detectors based on convolutional neural networks. The fundamentals of intracranial hemorrhage pathology and CT imaging as well as essential insight into computer vision and object detection are listed in this work. The knowledge of these fields of studies is a starting point for the implemenation of hemorrhage detector. The use of open-source CT image datasets is also discussed. The final part of this thesis is a model evaluation on a test dataset and results examination.
Thrombi detection in main brain arteries in CT image data
Líška, Martin ; Nemček, Jakub (referee) ; Chmelík, Jiří (advisor)
The master’s thesis deals with automatic preprocessing, segmentation and consecutive analysis of volume data of anonymized patient CTA acquisitions with an indication of stroke. Preprocessing of volume data is an essential step for proper vascular tree segmentation and analysis. The region growing method was used to segment the vascular tree of the brain. After extracting the vascular tree, the labeling of individual branches was applied in the algorithm and the appropriate features were extracted. The analysis examined the features of vessel lengths, their diameter and local brightness profiles, which are important indicators of possible stenosis or occlusion of the main vessels of the brain. The output of the algorithm are various modalities of diagnostic, assisted visualizations of the segmented vascular tree. The segmentation and analysis algorithm of cerebrovascular system was created in the MATLAB programming environment.
Detection and segmentation of lumbar vertebrae in 3D CT data
Nemček, Jakub ; Kolář, Radim (referee) ; Jakubíček, Roman (advisor)
This thesis deals with the detection and the segmentation of lumbar vertebrae in CT image datas. The described detection method is based on the use of a trained SVM classificator and histograms of oriented gradients as the image features. The detection method is applied on two-dimensional sagital slices of the CT image. The segmentation method is implemented as triangular mesh model deformation of models, that are obtained from averaged vertebrae in real CT datas. The first part of the thesis describes essential theoretical knowledge about the anatomy of the axial skeleton, computer tomography, image processing methods and about the detection and segmentation issues. The second part contains the algorithms realisation description, the evaluation and the discussion of the results. Applications of the algorithms in CAD systems is described at the end. The application of all of the points is done in the programming software Matlab.
Image segmentation of spinal disc in medical imaging
Meloun, Jan ; Nemček, Jakub (referee) ; Mézl, Martin (advisor)
The thesis is focused on the segmentation of the intervertebral disc in the image data.The introduction deals with the issue of the spine, the herniation of the intervertebraldisc. It also deals with imaging modalities, especially computed tomography and mag-netic resonance imaging. The practical part describes the image data segmentation andthe implementation of three of the published segmentation methods.
Detection of intracranial hemorrhages in head CT data
Nemček, Jakub ; Jan, Jiří (referee) ; Jakubíček, Roman (advisor)
This thesis deals with the detection of intracranial haemorrhages and their type classification in head CT images. The method of haemorrhages detection is based on a series of classifiers of the presence and type of haemorrhages in 2D CT slices in axial, sagittal and coronal plane, that may localise the bleedings and determine their types. The classifiers are based on the convolutional neural network architecture Inception-ResNet-v2. The head CT dataset CQ500 which is made available for public access, is used for the experiments. The thesis describes an additional manual annotation of the data, as the available annotations are insufficient for the purposes of the experiments. This thesis includes a theoretical basis of the essential medical knowledge, machine learning based classification and detection methods, and the detection algorithm proposal, realisation and testing. The algorithm performance is evaluated and discussed together with the potential implementation of the algorithm in computer-aided diagnosis systems.
Image segmentation of spinal disc in medical imaging
Meloun, Jan ; Nemček, Jakub (referee) ; Mézl, Martin (advisor)
This thesis is focused on segmentation of intervertebral discs in images from two medical imaging modalities - computed tomography (CT) and magnetic resonance imaging (MRI). Theoretical introduction of the thesis describes intervertebral disc herniation and relevant imaging modalities. It also includes description of basic and advanced segmentation methods. For practical part of the thesis, three different segmentation teqniques (one for CT data and two for MRI images) have been chosen, implemented and applied on images acquired at Radiodiagnostic department of Havlíčkův Brod hospital. The segmentation quality has been assessed quantitatively for individual methods by comparing the segmentation results to manually created reference segmentation of intervertebral discs.
Designing an automated workplace for charge and high-impedance measurement
Nemček, Jakub ; Bartušek, Karel (referee) ; Gescheidtová, Eva (advisor)
This barchelor thesis is about Desig an automated workplace forchargeable and high-impedant measurements. This automated workplace is realized by tubular aspiration capacitor, which is connected via differential converter U/I to data acquisition switch unit HP 34970A. The data acquisition switch unit HP 34970A is also connected by serial line RS-232 to Computer (PC), on which the directed program Agilent VEE Pro 7.0 is installed. To the right connection data acquisition switch unit HP 34970A and PC is necessary to set the same parameters on data acquisition switch unit HP 34970A, such in I/O config and also in Instrument manager too. In Instrument manager is requisite to set Plug und Play driver for data acquisition switch unit HP 34970A. The programing in Agilent VEE Pro 7.0 is based on object oriented programming. To start the program press the button “START“ and automatic measuring of concentration air ionts, will start the process (the trend is marked to the graph). The program is indicated if the ventilator blows an air in the aspiration capacitor and draws the trend of voltage on this ventilator to the graph. To stop the program press the buton “STOP“. Measured data are exported to program Excel. For the export Excel has to be running before the process. The function is verifing by measuring of background negativ a positiv ionts, by influence of position the source of ionts behind the aspiration capacitor and by influence of materials (metal plate, paper carton, wood, conductive paint) to the concentration of negativ ionts.
Intracranial hemorrhage localization in axial slices of head CT images
Kopečný, Kryštof ; Chmelík, Jiří (referee) ; Nemček, Jakub (advisor)
This thesis is focused on detection of intracranial hemorrhage in CT images using both one-stage and two-stage object detectors based on convolutional neural networks. The fundamentals of intracranial hemorrhage pathology and CT imaging as well as essential insight into computer vision and object detection are listed in this work. The knowledge of these fields of studies is a starting point for the implemenation of hemorrhage detector. The use of open-source CT image datasets is also discussed. The final part of this thesis is a model evaluation on a test dataset and results examination.
Thrombi detection in main brain arteries in CT image data
Líška, Martin ; Nemček, Jakub (referee) ; Chmelík, Jiří (advisor)
The master’s thesis deals with automatic preprocessing, segmentation and consecutive analysis of volume data of anonymized patient CTA acquisitions with an indication of stroke. Preprocessing of volume data is an essential step for proper vascular tree segmentation and analysis. The region growing method was used to segment the vascular tree of the brain. After extracting the vascular tree, the labeling of individual branches was applied in the algorithm and the appropriate features were extracted. The analysis examined the features of vessel lengths, their diameter and local brightness profiles, which are important indicators of possible stenosis or occlusion of the main vessels of the brain. The output of the algorithm are various modalities of diagnostic, assisted visualizations of the segmented vascular tree. The segmentation and analysis algorithm of cerebrovascular system was created in the MATLAB programming environment.
Image segmentation of spinal disc in medical imaging
Meloun, Jan ; Nemček, Jakub (referee) ; Mézl, Martin (advisor)
This thesis is focused on segmentation of intervertebral discs in images from two medical imaging modalities - computed tomography (CT) and magnetic resonance imaging (MRI). Theoretical introduction of the thesis describes intervertebral disc herniation and relevant imaging modalities. It also includes description of basic and advanced segmentation methods. For practical part of the thesis, three different segmentation teqniques (one for CT data and two for MRI images) have been chosen, implemented and applied on images acquired at Radiodiagnostic department of Havlíčkův Brod hospital. The segmentation quality has been assessed quantitatively for individual methods by comparing the segmentation results to manually created reference segmentation of intervertebral discs.

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8 Nemcek, Jakub
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