This research delves into the world of lung disease, specifically CT-detected emphysema, in the general population and those at high risk. Emphysema is not only a health concern on its own but also increases the risk of developing lung cancer. Therefore, it is crucial to assess the presence and severity of emphysema on CT scans, whether in a clinical or screening context. The thesis also looks into how the way we acquire and process CT scans can affect our ability to detect and measure emphysema accurately. The findings suggest that we can significantly reduce the radiation dose used in CT scans, up to 85%, by employing noise filtering methods. This reduction in radiation dose does not compromise the quality of the images. Furthermore, the ...
The aim of this review is to provide clinicians and technicians with an overview of the development ...
Purpose: We aimed to identify clinically relevant deep learning algorithms for emphysema quantificat...
Purpose: Phantom studies in CT emphysema quantification show that iterative reconstruction and deep ...
This research delves into the world of lung disease, specifically CT-detected emphysema, in the gene...
Population screening for emphysema and lung cancer using CTScreening for lung cancer using CT is an ...
Objective: The aim of this phantom study was to investigate the effect of scan parameters and noise ...
De NELSON-screeningsmethode voor longkanker is efficiënt om longkanker op te sporen, en vermindert h...
The objective of this study is to evaluate the feasibility of a disease-specific deep learning (DL) ...
Lung cancer is the most common cause of cancer-related death in the world. The Dutch-Belgian Randomi...
Purpose: Phantom studies in CT emphysema quantification show that iterative reconstruction and deep ...
In areas with a high intrinsic contrast such as the chest, radiation dose can be reduced for specifi...
The aim of this review is to provide clinicians and technicians with an overview of the development ...
Purpose: We aimed to identify clinically relevant deep learning algorithms for emphysema quantificat...
Purpose: Phantom studies in CT emphysema quantification show that iterative reconstruction and deep ...
This research delves into the world of lung disease, specifically CT-detected emphysema, in the gene...
Population screening for emphysema and lung cancer using CTScreening for lung cancer using CT is an ...
Objective: The aim of this phantom study was to investigate the effect of scan parameters and noise ...
De NELSON-screeningsmethode voor longkanker is efficiënt om longkanker op te sporen, en vermindert h...
The objective of this study is to evaluate the feasibility of a disease-specific deep learning (DL) ...
Lung cancer is the most common cause of cancer-related death in the world. The Dutch-Belgian Randomi...
Purpose: Phantom studies in CT emphysema quantification show that iterative reconstruction and deep ...
In areas with a high intrinsic contrast such as the chest, radiation dose can be reduced for specifi...
The aim of this review is to provide clinicians and technicians with an overview of the development ...
Purpose: We aimed to identify clinically relevant deep learning algorithms for emphysema quantificat...
Purpose: Phantom studies in CT emphysema quantification show that iterative reconstruction and deep ...