AI Medical Compendium Topic:
Contrast Media

Clear Filters Showing 491 to 500 of 512 articles

Deep learning assisted differentiation of hepatocellular carcinoma from focal liver lesions: choice of four-phase and three-phase CT imaging protocol.

Abdominal radiology (New York)
PURPOSE: To evaluate whether a three-phase dynamic contrast-enhanced CT protocol, when combined with a deep learning model, has similar accuracy in differentiating hepatocellular carcinoma (HCC) from other focal liver lesions (FLLs) compared with a f...

Machine Learning and Deep Neural Networks: Applications in Patient and Scan Preparation, Contrast Medium, and Radiation Dose Optimization.

Journal of thoracic imaging
Artificial intelligence (AI) algorithms are dependent on a high amount of robust data and the application of appropriate computational power and software. AI offers the potential for major changes in cardiothoracic imaging. Beyond image processing, m...

[Late gadolinium enhancement and T1 mapping for the diagnosis of cardiac amyloidosis].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To explore the role of late gadolinium enhancement (LGE) and T1 mapping for detection of cardiac amyloidosis.

Classification of Aortic Dissection and Rupture on Post-contrast CT Images Using a Convolutional Neural Network.

Journal of digital imaging
Aortic dissections and ruptures are life-threatening injuries that must be immediately treated. Our national radiology practice receives dozens of these cases each month, but no automated process is currently available to check for critical pathologi...

Deep convolutional neural network for reduction of contrast-enhanced region on CT images.

Journal of radiation research
This study aims to produce non-contrast computed tomography (CT) images using a deep convolutional neural network (CNN) for imaging. Twenty-nine patients were selected. CT images were acquired without and with a contrast enhancement medium. The trans...