Addressing the Contrast Media Recognition Challenge: A Fully Automated Machine Learning Approach for Predicting Contrast Phases in CT Imaging.

Giulia BaldiniRené HoschCynthia S SchmidtKatarzyna BorysLennard KrollSven KoitkaPatrizia HauboldObioma PelkaFelix NensaJohannes Haubold

Published in: Investigative radiology (2024)

The integration of open-source segmentation networks and classifiers effectively classified contrast phases and identified GIT contrast enhancement using anatomical landmarks.

Keyphrases

magnetic resonance
machine learning
contrast enhanced
deep learning
magnetic resonance imaging
computed tomography
high resolution
artificial intelligence
convolutional neural network
mass spectrometry
image quality
photodynamic therapy