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Design of a Crash-Test Dummy
Sedláčková, Martina ; Coufal, Tomáš (referee) ; Bilík, Martin (advisor)
The main objective of this thesis is construction of crash test dummy for vehicle-pedestrian crash tests. There is review of nowadays used crash test dummies types in the introduction of this thesis. This is followed by part describing construction itself. Chapter about construction begins by characterizing of used materials features in relation with real human body physiology. Main part of chapter is describing construction of crash test dummy’s skeleton and its individual components including 3D modelling and strength analysis. Thesis is finished by cost assessment.
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Identification of vertebrae type in CT data by machine learning methods
Matoušková, Barbora ; Kolář, Radim (referee) ; Chmelík, Jiří (advisor)
Identification of vertebrae type by machine learning is an important task to facilitate the work of medical doctors. This task is embarrassed by many factors. First, a spinal CT imagining is usually performed on patiens with pathologies such as lesions, tumors, kyphosis, lordosis, scoliosis or patients with various implants that cause artifacts in the images. Furthermore, the neighboring vertebraes are very similar which also complicates this task. This paper deals with already segmented vertebrae classification into cervical, thoracic and lumbar groups. Support vector machines (SVM) and convolutional neural networks (CNN) AlexNet and VGG16 are used for classification. The results are compared in the conclusion.
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Time development analysis of treated lesion in spinal CT data
Nohel, Michal ; Jan, Jiří (referee) ; Jakubíček, Roman (advisor)
This diploma thesis is focused on time-development analysis of treated lesion in CT data. The theoretical part of the thesis deals with the anatomy, physiology, and pathophysiology of the spine and vertebral bodies. It further describes diagnostic and therapeutic options for the detection and treatment of spinal lesions. It contains an overview of the current state of usage of time-development analysis in oncology. The problems of the available databases are discussed and new databases are created for subsequent analysis. Futhermore, the methodology of time-development analysis according to the shape characterization and the size of the vertebral involvement is proposed. The proposed methodological approaches to feature extraction are applied to the created databases. Their choice and suitability is discussed, including their potential for possible usege in clinical practice of monitoring the development and derivation of characteristic dependences of features on the patient's prognosis.
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Methods of Detection, Segmentation and Classification of Difficult to Define Bone Tumor Lesions in 3D CT Data
Chmelík, Jiří ; Flusser,, Jan (referee) ; Kozubek, Michal (referee) ; Jan, Jiří (advisor)
The aim of this work was the development of algorithms for detection segmentation and classification of difficult to define bone metastatic cancerous lesions from spinal CT image data. For this purpose, the patient database was created and annotated by medical experts. Successively, three methods were proposed and developed; the first of them is based on the reworking and combination of methods developed during the preceding project phase, the second method is a fast variant based on the fuzzy k-means cluster analysis, the third method uses modern machine learning algorithms, specifically deep learning of convolutional neural networks. Further, an approach that elaborates the results by a subsequent random forest based meta-analysis of detected lesion candidates was proposed. The achieved results were objectively evaluated and compared with results achieved by algorithms published by other authors. The evaluation was done by two objective methodologies, technical voxel-based and clinical object-based ones. The achieved results were subsequently evaluated and discussed.
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Stress-strain analysis of spinal segment with fixator
Mach, Ondřej ; Valášek, Jiří (referee) ; Marcián, Petr (advisor)
This Master’s thesis deals with strain-stress analysis of a spine segment with an introduced fixator and a spine in natural physiological state. The work starts with a research study of literature sources that focus on similar issues. Furthermore, basic anatomy terminology and basic procedures for human spine stabilization were described. The formulated issue was resolved by computational modelling with the use of the finite element method. This solution requires a suitable computational model to be produced. This model consists of partial geometry, material, bond, and loading models. The geometric model was produced on the basis of CT scan images of a 60-year-old man which were used for producing five spine vertebrae T11–L3. Moreover, the geometric model consists of four intervertebral discs and eight articular cartilages. The material model includes homogeneous, heterogeneous and degraded properties of bone tissue. The strain-stress analysis was performed for seven loading states, which concern basic movements of human spine – standing, bending forward, bending backwards, bending left, bending right, left rotation and right rotation, with the use of ANSYS software. The assessed and analysed quantities include spine segment displacement, contact pressure of articular cartilages and stress on the fixator.
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Code Generation Using Design Patterns
Hanák, František ; Malinka, Kamil (referee) ; Jurnečka, Peter (advisor)
This thesis describes code generation using design patterns. It deals with questions of specification of design patterns and their usage in code generation. The main part of thesis follows describtions of design patterns, their categorization, usage purpose and main ways of design patterns definitions. It describes the most often used formal design patterns specifications, their possible usage in code generation and design of algorithm for searching similar structures of patterns in source code in detail.
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Meta-analysis of bone tumorous lesions in spinal CT data using convolutional neural networks
Nantl, Ondřej ; Jakubíček, Roman (referee) ; Chmelík, Jiří (advisor)
This bachelor thesis deals with the use of convolutional neural networks in the meta-analysis of bone tumor lesions in CT image data. The theoretical part describes the anatomy and pathology of bone tissue, machine learning, discusses the functionality of convolutional neural networks and summarizes selected existing methods for computer-aided diagnosis of vertebra bone lesions. In the practical part, various types of models using convolutional neural networks were implemented and the networks were trained on an available augmented dataset. Finally, the results of various types of models were statistically evaluated, compared with available articles and discussed.
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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.
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Vertebra detection and identification in CT oncological data
Věžníková, Romana ; Harabiš, Vratislav (referee) ; Jakubíček, Roman (advisor)
Automated spine or vertebra detection and segmentation from CT images is a difficult task for several reasons. One of the reasons is unclear vertebra boundaries and indistinct boundaries between vertebra. Next reason is artifacts in images and high degree of anatomical complexity. This paper describes the design and implementation of vertebra detection and classification in CT images of cancer patients, which adds to the complexity because some of vertebrae are deformed. For the vertebra segmentation, the Otsu’s method is used. Vertebra detection is based on search of borders between individual vertebra in sagittal planes. Decision trees or the generalized Hough transform is applied for the identification whereas the vertebra searching is based on similarity between each vertebra model shape and planes of CT scans.
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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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