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Application, analysis and evaluation of a novel medical image annotation and segmentation tools
Sucháček, Jan ; Paštěka, Richard (referee) ; Dr.Benjamin Ramberger, MSc. BSc. BSc. (advisor)
This thesis explores the creation of 3D models of the human upper airways from CT scans to enhance the understanding of complex anatomical details of the upper airways, assist in detecting pathological changes, and facilitate therapeutic decision-making. These models also enable simulation and assessment of airflow characteristics within the human upper airways. To generate these 3D models, two annotation and three segmentation methods were employed on a dataset of six patient CT scans. Various metrics, such as the number of triangles, surface area, volume, model intersection volume, Dice coefficient, and modelto-model distance, were calculated for all resulting 3D models to characterize the models and compare the methods. A detailed analysis focused on four anatomical parts: the nasal cavity with sinuses, pharynx, larynx, and trachea, was performed. Additionally, a computational fluid dynamics (CFD) simulation was conducted on one model to analyze airflow in the upper airways during breathing. This simulation provided insights into airflow dynamics inside the upper airways, potentially reducing the need for invasive examinations. The findings of this thesis demonstrate the potential of 3D upper airway models to improve diagnostic accuracy, treatment planning, and patient outcomes in respiratory medicine.and compare the methods. A detailed analysis focused on four anatomical parts: the nasal cavity with sinuses, pharynx, larynx, and trachea, was performed. Additionally, a computational fluid dynamics (CFD) simulation was conducted on one model to analyze airflow in the upper airways during breathing. This simulation provided insights into airflow dynamics inside the upper airways, potentially reducing the need for invasive examinations. The findings of this thesis demonstrate the potential of 3D upper airway models to improve diagnostic accuracy, treatment planning, and patient outcomes in respiratory medicine.
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