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Segmentation of amyloid plaques in brains of trangenic rats based on microCT image data
Kačníková, Diana ; Kolář, Radim (referee) ; Chmelík, Jiří (advisor)
The presence of amyloid plaques in the hippocampus highlights the incidence of Alzheimer’s disease. Manual segmentation of amyloid plaques is very time consuming and increases the time that can be used to monitor the distribution of amyloid plaques. Distribution carries significant information about disease progression and the impact of potential therapy. The automatic or semi-automatic segmentation method can lead to significant savings in the time which are required when the disease has rapid progression. The description of amyloid plaques and the computed tomography are included in this work. In this diploma thesis are three implemented algorithms, two of them are based on published articles and one’s own methodological solution. The conclusion of the thesis is a quantitative evaluation of the accuracy of implemented segmentation procedures.
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Comparison of data from smartphones, fitness trackers, and specialised devices
Kačníková, Diana ; Smital, Lukáš (referee) ; Němcová, Andrea (advisor)
The focus of this thesis is the comparissement of data from smart phones, fitness bracelets and specialized devices. Thesis includes description of features when using special devices such as smart phone, Axivity AX3 bracelet and Fitbit Alta HR for data recording. Signals were recorded using those devices with different anatomical locations and sampling frequencies. Those data recorded were implemented for three algorithms created for activity classification. Detection accuracy was calculated for each signal recorded. Devices, sampling frequencies and anatomical locations were compared based on the accuracy. Ultimate combination of sampling frequency, anatomical location and suitable device was defined.
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Segmentation of amyloid plaques in brains of trangenic rats based on microCT image data
Kačníková, Diana ; Kolář, Radim (referee) ; Chmelík, Jiří (advisor)
The presence of amyloid plaques in the hippocampus highlights the incidence of Alzheimer’s disease. Manual segmentation of amyloid plaques is very time consuming and increases the time that can be used to monitor the distribution of amyloid plaques. Distribution carries significant information about disease progression and the impact of potential therapy. The automatic or semi-automatic segmentation method can lead to significant savings in the time which are required when the disease has rapid progression. The description of amyloid plaques and the computed tomography are included in this work. In this diploma thesis are three implemented algorithms, two of them are based on published articles and one’s own methodological solution. The conclusion of the thesis is a quantitative evaluation of the accuracy of implemented segmentation procedures.
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Comparison Of Data From Smartphones And
Specialised Devices
Kačníková, Diana
The aim of this study is to introduce two algorithms for physical activity recognition and to compare various devices such as smartphones and specialized devices using these algorithms. Signals are recorded using smartphones and accelerometer Axivity AX3. In the first part of the report, classification algorithms are described. In the second part algorithms are tested using recorded signals and the last part provides comparison of above mentioned tested devices.
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Comparison of data from smartphones, fitness trackers, and specialised devices
Kačníková, Diana ; Smital, Lukáš (referee) ; Němcová, Andrea (advisor)
The focus of this thesis is the comparissement of data from smart phones, fitness bracelets and specialized devices. Thesis includes description of features when using special devices such as smart phone, Axivity AX3 bracelet and Fitbit Alta HR for data recording. Signals were recorded using those devices with different anatomical locations and sampling frequencies. Those data recorded were implemented for three algorithms created for activity classification. Detection accuracy was calculated for each signal recorded. Devices, sampling frequencies and anatomical locations were compared based on the accuracy. Ultimate combination of sampling frequency, anatomical location and suitable device was defined.
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