BACKGROUND: Computed tomography angiography (CTA) provides significant information on image quality in vascular imaging, thus offering high-resolution images despite having the disadvantages of increased radiation doses and contrast agent-related sid...
BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thick...
BACKGROUND: Intracranial hemorrhages (ICH) are life-threatening conditions that require rapid detection and precise subtype classification. Automated segmentation and volumetric analysis using deep learning can enhance clinical decision-making.
ObjectiveThe goal of this study is to assess the effectiveness of a hybrid deep learning model that combines 3D Auto-encoders with attention mechanisms to detect lung cancer early from CT scan images. The study aims to improve diagnostic accuracy, se...
BACKGROUND: Automatic segmentation of thymic lesions in preoperative computed tomography (CT) images is crucial for accurate diagnosis but remains time-consuming. Although UNet is widely used in medical imaging, its performance is limited by the inhe...
BACKGROUND: This study employed a convolutional neural network (CNN) to analyze computed tomography (CT) scans with the aim of differentiating among renal tumors according to histologic sub-type.
Journal of cardiovascular computed tomography
39988511
BACKGROUND: As a new noninvasive diagnostic technique, computed tomography-derived fraction flow reserve (FFRCT) has been used to identify hemodynamically significant coronary artery stenosis. FFRCT can be calculated using computational fluid dynamic...
International journal of computer assisted radiology and surgery
39985731
PURPOSE: The paper introduces a novel two-step network based on semi-supervised learning for intestine segmentation from CT volumes. The intestine folds in the abdomen with complex spatial structures and contact with neighboring organs that bring dif...
PURPOSE: Pulmonary hypertension (PH) is a complex disease classified into five groups (I-V) by the European Society of Cardiology/European Respiratory Society (ESC/ERS) guidelines. Chest contrast-enhanced computed tomography (CECT) is crucial in the ...
OBJECTIVE: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for full-field digital mammography (FFDM) when applied to synthetic mammography (SM).