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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

Profile image for René Pallenberg

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.