In this paper, an automated method for the detection, segmentation and classification of Abdominal Aortic Aneurysm (AAA) region in computed tomography (CT) images is introduced. Deep Belief Network (DBN) is applied for the purpose of AAA detection and severity classification in this study. Optimum parameters for training the DBN are determined for the training data from the selected dataset. AAA region can be successfully segmented from the CT images and the result is comparable to the existing methods
A Combined Deep Learning System for Automatic Detection of “Bovine” Aortic Arch on Computed Tomograp...
Precise automatic vertebra segmentation in computed tomography (CT) images is important for the quan...
BACKGROUND AND PURPOSE: The rupture of an intracranial aneurysm is a serious incident, causing subar...
This study is focused on developing an automated algorithm for the detection and segmentation of Abd...
Abdominal aortic aneurysms (AAA) may remain clinically silent until they enlarge and patients presen...
Abdominal aortic aneurysms (AAAs) are dilations in the descending aorta which can result in interna...
Purpose: Although segmentation of Abdominal Aortic Aneurysms (AAA) thrombus is a crucial step for bo...
Computational hemodynamics is increasingly used to quantify hemodynamic characteristics in and aroun...
An abdominal aortic aneurysm (AAA) is a dangerous cardiovascular disease that can cause serious heal...
Computer-aided detection (CAD) systems, which automatically detect and indicate location of potentia...
Introduction: Visceral arterial aneurysms (VAAs) are life threatening. Due to the paucity of symptom...
An abdominal aortic aneurysm (AAA) is a focal dilation of the aorta that may lead to its rupture. Th...
Medical imaging examination on patients usually involves more than one imaging modalities, such as C...
Background: Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive...
Digitalisation and the generation of large amounts of data from examinations and medical interventio...
A Combined Deep Learning System for Automatic Detection of “Bovine” Aortic Arch on Computed Tomograp...
Precise automatic vertebra segmentation in computed tomography (CT) images is important for the quan...
BACKGROUND AND PURPOSE: The rupture of an intracranial aneurysm is a serious incident, causing subar...
This study is focused on developing an automated algorithm for the detection and segmentation of Abd...
Abdominal aortic aneurysms (AAA) may remain clinically silent until they enlarge and patients presen...
Abdominal aortic aneurysms (AAAs) are dilations in the descending aorta which can result in interna...
Purpose: Although segmentation of Abdominal Aortic Aneurysms (AAA) thrombus is a crucial step for bo...
Computational hemodynamics is increasingly used to quantify hemodynamic characteristics in and aroun...
An abdominal aortic aneurysm (AAA) is a dangerous cardiovascular disease that can cause serious heal...
Computer-aided detection (CAD) systems, which automatically detect and indicate location of potentia...
Introduction: Visceral arterial aneurysms (VAAs) are life threatening. Due to the paucity of symptom...
An abdominal aortic aneurysm (AAA) is a focal dilation of the aorta that may lead to its rupture. Th...
Medical imaging examination on patients usually involves more than one imaging modalities, such as C...
Background: Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive...
Digitalisation and the generation of large amounts of data from examinations and medical interventio...
A Combined Deep Learning System for Automatic Detection of “Bovine” Aortic Arch on Computed Tomograp...
Precise automatic vertebra segmentation in computed tomography (CT) images is important for the quan...
BACKGROUND AND PURPOSE: The rupture of an intracranial aneurysm is a serious incident, causing subar...