Journal of vascular and interventional radiology : JVIR
Feb 12, 2024
PURPOSE: To validate the sensitivity and specificity of a 3-dimensional (3D) convolutional neural network (CNN) artificial intelligence (AI) software for lung lesion detection and to establish concordance between AI-generated needle paths and those u...
PURPOSE: Identifying factors predicting the spontaneous passage of distal ureteral stones and evaluating the effectiveness of artificial intelligence in prediction.
PURPOSE: To predict hematoma growth in intracerebral hemorrhage patients by combining clinical findings with non-contrast CT imaging features analyzed through deep learning.
BACKGROUND: Notwithstanding the encouraging results of previous studies reporting on the efficiency of deep learning (DL) in COVID-19 prognostication, clinical adoption of the developed methodology still needs to be improved. To overcome this limitat...
Journal of imaging informatics in medicine
Feb 9, 2024
Drowning diagnosis is a complicated process in the autopsy, even with the assistance of autopsy imaging and the on-site information from where the body was found. Previous studies have developed well-performed deep learning (DL) models for drowning d...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 9, 2024
The extraction of abdominal structures using deep learning has recently experienced a widespread interest in medical image analysis. Automatic abdominal organ and vessel segmentation is highly desirable to guide clinicians in computer-assisted diagno...
International journal of legal medicine
Feb 8, 2024
During the last years, the detection of different causes of death based on postmortem imaging findings became more and more relevant. Especially postmortem computed tomography (PMCT) as a non-invasive, relatively cheap, and fast technique is progress...
Medical & biological engineering & computing
Feb 8, 2024
Early intervention in tumors can greatly improve human survival rates. With the development of deep learning technology, automatic image segmentation has taken a prominent role in the field of medical image analysis. Manually segmenting kidneys on CT...
BACKGROUND:: Efficient and accurate delineation of organs at risk (OARs) is a critical procedure for treatment planning and dose evaluation. Deep learning-based auto-segmentation of OARs has shown promising results and is increasingly being used in r...
The objectives are to improve the diagnostic efficiency and accuracy of epidemic pulmonary infectious diseases and to study the application of artificial intelligence (AI) in pulmonary infectious disease diagnosis and public health management. The co...
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