Now showing items 1-4 of 4
Automated segmentation of the injured spleen
Purpose: To develop a novel automated method for segmentation of the injured spleen using morphological properties following abdominal trauma. Average attenuation of a normal spleen in computed tomography (CT) does not ...
Automated computer-aided diagnosis of splenic lesions due to abdominal trauma
Background: Computer-aided detection in the setting of trauma presents unique challenges due to variations in shape and attenuation of the injured organs based on the timing and severity of the injury. We developed and ...
A CAD of fully automated colonic polyp detection for contrasted and non-contrasted CT scans
Computer-aided detection (CAD) systems are developed to help radiologists detect colonic polyps over CT scans. It is possible to reduce the detection time and increase the detection accuracy rates by using CAD systems. In ...
Automatic Detection of Pulmonary Embolism in CTA Images Using Machine Learning
(Kaunas Univ. Technology, 2017)
In this study, a novel computer-aided detection (CAD) method is introduced to detect pulmonary embolism (PE) in computed tomography angiography (CTA) images. This method consists of lung vessel segmentation, PE candidate ...