Amsterdam UMC
Julia Noothout Amsterdam UMC

PhD candidate
Phone: +31 20 56 60226

Julia Noothout obtained her Bachelor of Science degree in Medicine in 2013 from Utrecht University. In 2017 she received her Master of Science degree in Biomedical Image Sciences and with this combination of biomedical training and image processing related research she is able to combine her interest in functionality of the human body and medical imaging.

Her master thesis focused on segmentation of the aortic arch in low-dose chest CT by applying weakly supervised training for convolutional neural networks. In June 2017, Julia started her PhD at the Image Sciences Institute at UMC Utrecht and joined the Quantitative Medical Image Analysis Group. Her main research topic is Deep Transfer Learning techniques with an application to cardiac spectral CT.


J.M.H. Noothout, B.D. de Vos, J.M. Wolterink, E.M. Postma, P.A.M. Smeets, R.A.P. Takx, T. Leiner, M.A. Viergever, I. Išgum

Deep learning-based regression and classification for automatic landmark localization in medical images Journal Article

IEEE Transactions on Medical Imaging (in press), 2020.

Abstract | Links | BibTeX


J.M.H. Noothout, E.M. Postma, S. Boesveldt, B.D. de Vos, P.A.M. Smeets, I. Išgum

Automatic segmentation of the olfactory bulbs in MRI Inproceedings

SPIE Medical Imaging (in press), 2020.

Abstract | BibTeX


J.M.H. Noothout, B.D de Vos, J.M. Wolterink, T. Leiner, I. Isgum

CNN-based Landmark Detection in Cardiac CTA Scans Inproceedings

Medical Imaging with Deep Learning. MIDL Amsterdam, 2018.

Abstract | Links | BibTeX


Julia M.H. Noothout, Bob D. de Vos, Jelmer M. Wolterink, Richard A.P. Takx, Tim Leiner, Ivana Išgum

Deep Learning for Automatic Landmark Localization in CTA for Transcatheter Aortic Valve Implantation Conference

Radiological Society of North America, 105th Annual Meeting, 2019.

Abstract | Links | BibTeX