Random Forest and Gradient Boosted Trees for Patient Individualized Contrast Agent Dose Reduction in CT Angiography Passed
Wednesday May 24, 2023 11:15 - 11:30 G2
Lecturer: René Pallenberg
Track: MIE: Sensors, signals and Imaging Informatics
Language
English
Seminar type
On site only
Level of knowledge
Advanced
Conference
MIE
Authors
René Pallenberg, Marja Fleitmann, Andreas Martin Stroth, Alexander Fürschke, Jan Gerlach, Jörg Barkhausen, Arpad Bischof, Heinz Handels
Lecturers
René Pallenberg Lecturer
research associate
University of Lübeck
Hello, my name is René Pallenberg and I am a research associate at the Institute for Signal Processing at the University of Lübeck. I hold a Master of Science in Medical Informatics.
My research focuses on the processing of medical images and signals. One of my publications deals with the automatic quality measurement of aortic contrast-enhanced CT angiographies for patient-specific dose optimization.
I will be presenting my work titled “Random Forest and Gradient Boosted Trees for Patient Individualized Contrast Agent Dose Reduction in CT Angiography”. In this work, I investigate how clinical parameters can be used to predict the quality of a CT angiography. This could be used to selectively reduce the contrast agent dose in CT angiographies for individual patients.
I look forward to sharing my work with you and answering your questions.
[1] R. Pallenberg et al., “Automatic quality measurement of aortic contrast-enhanced CT angiographies for patient-specific dose optimization,” vol. 15, no. 10, pp. 1611–1617, 2020.