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Statistical properties of ultrasound images in contrast mode
Věžníková, Romana ; Kolář, Radim (referee) ; Slávik, Vladimír (advisor)
The bachelor’s thesis is focused on properties of ultrasound images in contrast mode. First of all it describes the basic properties of ultrasound, the way in which the ultrasonic signals are generated, the parameters of ultrasound and ultrasonic imaging modes. Next part deals with harmonic and contrast imaging modes. This part explains principles of these modes as well as the usage of contrast agents and artefacts connected with ultrasound imaging in contrast mode. The thesis also shows the approximation of the amplitude probability density function of ultrasonic images and description of its single models, out of which is chosen the RiIG model (Rician Inverse Gaussian distribution) for approximation of ultrasound images in this case. To gain parameters of amplitude probability density function from ultrasonic data in contrast imaging mode is made the application using Matlab programming environment. Thereafter is the thesis focused on determining equations for dependences of RiIG distribution parameters on known concentrations of contrast agent for ultrasonic data captured in vitro. These equations are useful for determining the unknown concentration of contrast agent used in images captured in vivo and making its dilution function.
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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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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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Statistical properties of ultrasound images in contrast mode
Věžníková, Romana ; Kolář, Radim (referee) ; Slávik, Vladimír (advisor)
The bachelor’s thesis is focused on properties of ultrasound images in contrast mode. First of all it describes the basic properties of ultrasound, the way in which the ultrasonic signals are generated, the parameters of ultrasound and ultrasonic imaging modes. Next part deals with harmonic and contrast imaging modes. This part explains principles of these modes as well as the usage of contrast agents and artefacts connected with ultrasound imaging in contrast mode. The thesis also shows the approximation of the amplitude probability density function of ultrasonic images and description of its single models, out of which is chosen the RiIG model (Rician Inverse Gaussian distribution) for approximation of ultrasound images in this case. To gain parameters of amplitude probability density function from ultrasonic data in contrast imaging mode is made the application using Matlab programming environment. Thereafter is the thesis focused on determining equations for dependences of RiIG distribution parameters on known concentrations of contrast agent for ultrasonic data captured in vitro. These equations are useful for determining the unknown concentration of contrast agent used in images captured in vivo and making its dilution function.
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