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Long-term Analysis of Ultrasound Video Sequences Using Interest Point Detectors
Zukal, Martin ; Závodná, Eva (referee) ; Papež,, Václav (referee) ; Říha, Kamil (advisor)
This doctoral thesis deals with the analysis of ultrasound (US) video sequences. It specifically focuses on long-term tracking of the common carotid artery (CCA) in transversal section and measurement of its geometric parameters in a sequence of US images. The design and implementation of a system for automatic tracking of the artery is described in this thesis. The proposed system utilizes Viola-Jones detector and Hough transform to localize the artery in the image. Interest points are detected in the area of the artery wall. These points are then tracked using optical flow. The proposed system comprises a number of innovative methods which allow to perform accurate long-term measurement of parameters of CCA and store the results. A novel mathematical model describing the movement of CCA in transversal section during a cardiac cycle is defined afterwards taking the influence of breathing into consideration. A number of artificial sequences of US images based on this model have been created. These sequences were consequently used to evaluate the accuracy of the proposed system in terms of measuring the parameters of CCA. The sequences are unique because of their length which makes them suitable for evaluation of tracking accuracy even in long video sequences.
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Object similarity detection
Přidal, Oldřich ; Gogol, František (referee) ; Richter, Miloslav (advisor)
The aim of this thesis was to make a program for object finding, object segmentation and similarity object detection in the image. Object are representing by cars. Description of image making, image preprocessing, geometrical transform and Hough transform was written in the theoretical part of the thesis. Also basic morphological operations, corner detection algorithms and methods of object similarity detection were described in this part. The practical part of the thesis focus to realization of single segments from how to make image, through main program analysis and auxiliary functions to similarity results evaluation. Main program is devided to four parts. The program is preprocessed in the first part. The geometrical transforms are used in the second part and the object similarity is detected in the third part. The last part shows the results. The algorithm is realized in C++ language using the OpenCV library.
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Long-term Analysis of Ultrasound Video Sequences Using Interest Point Detectors
Zukal, Martin ; Závodná, Eva (referee) ; Papež,, Václav (referee) ; Říha, Kamil (advisor)
This doctoral thesis deals with the analysis of ultrasound (US) video sequences. It specifically focuses on long-term tracking of the common carotid artery (CCA) in transversal section and measurement of its geometric parameters in a sequence of US images. The design and implementation of a system for automatic tracking of the artery is described in this thesis. The proposed system utilizes Viola-Jones detector and Hough transform to localize the artery in the image. Interest points are detected in the area of the artery wall. These points are then tracked using optical flow. The proposed system comprises a number of innovative methods which allow to perform accurate long-term measurement of parameters of CCA and store the results. A novel mathematical model describing the movement of CCA in transversal section during a cardiac cycle is defined afterwards taking the influence of breathing into consideration. A number of artificial sequences of US images based on this model have been created. These sequences were consequently used to evaluate the accuracy of the proposed system in terms of measuring the parameters of CCA. The sequences are unique because of their length which makes them suitable for evaluation of tracking accuracy even in long video sequences.
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Object similarity detection
Přidal, Oldřich ; Gogol, František (referee) ; Richter, Miloslav (advisor)
The aim of this thesis was to make a program for object finding, object segmentation and similarity object detection in the image. Object are representing by cars. Description of image making, image preprocessing, geometrical transform and Hough transform was written in the theoretical part of the thesis. Also basic morphological operations, corner detection algorithms and methods of object similarity detection were described in this part. The practical part of the thesis focus to realization of single segments from how to make image, through main program analysis and auxiliary functions to similarity results evaluation. Main program is devided to four parts. The program is preprocessed in the first part. The geometrical transforms are used in the second part and the object similarity is detected in the third part. The last part shows the results. The algorithm is realized in C++ language using the OpenCV library.
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