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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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Multiple sclerosis detection
Kopuletý, Michal ; Mangová, Marie (referee) ; Uher, Václav (advisor)
This thesis is focused on detecting multiple sclerosis lesions from magnetic resonance images. Correctly retrieved lesions are very important for medical diagnosis. Detection of lesions using machine learning techniques is quite challenging because of large variability in size, shape and position of lesions in the brain. In the practical part is designed base software, which after completion will classify pixels, so that is possible to find lesions of multiple sclerosis. For classification will be used Support vector machine. Theoretical part describes multiple sclerosis, basic operations performed with biomedical images and data classification.
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Usury and Lesion in Business Law Realtions
Šejko, Jaroslav ; Černá, Stanislava (advisor) ; Pelikán, Robert (referee)
Usury and Lesion in Business Law Realtions Abstract The main objective of the thesis is to investigate the issue of usury and lesion in business law realtions and to analyse the possibilities that entrepreneurs have to protect themselves from these undesirable phenomena by means of legal institutes of private law. Particular emphasis is placed on the relationship between the general private law remedies, which serve to correct the substantive incorrectness of legal actions, and the special provisions that exclude protection of entrepreneurs against usury and lesion. In the course of the thesis we will focus on the evaluation and analysis of these institutes and their possible impact on business entities in business dealings, including a comparison with foreign legislation (mainly German and Austrian) and practical recommendations. In its examination, the thesis is progressively divided into several subparts, with the first topic addressed being the protection of the weaker party, the definition of the situation and the reasons for the protection of the weaker party, including the ideological background. The emphasis in this chapter is on the entrepreneur as the weaker party and the possible abuse of the stronger position. In the second and third parts, I focus on the definition of the concepts of usury and...
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Methodology Of Time-Development Analysis Of Vertebral Tumors In Ct Data
Nohel, Michal
This paper presents the methodology of time-development analysis of vertebral tumors inCT data. It including an overview of suitable features which can relevantly characterize the shape oftumor tissue. We proposed two different analysis methodologies: for compact tumors and the wholevertebral body. The test database of five lytic compact tumors containing five follow ups was created.The initial result of time-development for statistical features for compact tumors on created databaseand whole body vertebra were shown.
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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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Casuistry of physiotherapy care of patient after plastic reconstruction of anterior and posterior cruciate ligament of knee joint
Vrablíková, Gabriela ; Říha, Michal (advisor) ; Hlavičková, Růžena (referee)
Title: Casuistry of physiotherapy care of patient after plastic reconstruction of anterior and posterior cruciate ligament of knee joint Objectives: To summarise theoretic knowledge about knee joint soft structures injury and the possibilities of its therapy, especially physiotherapy care after plastic reconstruction of the ligaments. Then, to present casuistry of the patient after plastic reconstruction of anterior and posterior cruciate ligament. Summary: Thesis consists of two parts - general and special. In the general part, theoretic information about injuries of soft structures of the knee joint is summarised, as well as overview of posibilities of its examination (especially special tests) and therapy, both conservative and operative. The special part presents a casuistry of physiotherapy care of patient after plastic reconstruction of anterior and posterior ligament of the knee joint. Author worked with this patient while practising in Military University Hospital in Prague, since 2014-01-21 to 2014-01-31. By the means of special rehabilitation we achieve in operated knee joint decreasing of swelling, increasing of range of motion, strenghtening of weakened muscles, restoration of joint play and improving of other parameters. Thus we achieve overall better dynamic stabilization of operated...
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Multiple sclerosis detection
Kopuletý, Michal ; Mangová, Marie (referee) ; Uher, Václav (advisor)
This thesis is focused on detecting multiple sclerosis lesions from magnetic resonance images. Correctly retrieved lesions are very important for medical diagnosis. Detection of lesions using machine learning techniques is quite challenging because of large variability in size, shape and position of lesions in the brain. In the practical part is designed base software, which after completion will classify pixels, so that is possible to find lesions of multiple sclerosis. For classification will be used Support vector machine. Theoretical part describes multiple sclerosis, basic operations performed with biomedical images and data classification.
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