Florian Dubost, MSc.

Florian Dubost

Office: Na 26-14
Phone: +31-10-7044118
Email: f.dubost@erasmusmc.nl, floriandubost1@gmail.com
Website: Google Scholar Researchgate LinkedIn

Curriculum Vitae

Florian Dubost is PhD student in medical image analysis at Erasmus Medical Center Rotterdam, the Netherlands.

Florian was born in 1992 in France. He started his studies in 2010 in the CPGE Janson de Sailly in Paris, joined the Ecole Centrale Marseille (ECM) in 2012 and the Technical University of Munich (TUM) in 2014 for a double-degree program.
In 2016 he received his two Master’s degrees in Science in Engineering (ECM) and Medical Engineering (TUM).

During his studies Florian was involved in several machine learning projects applied to medical data. He worked under the supervision of Prof. Navab (TUM) and Prof. Ralaivola (LIF - Marseille).

The topic of his research is brain segmentation of Cerebral Microbleeds and Virchow-Robin Spaces. His research interests are machine learning and computer vision techniques applied to medical data.

Research lines

Model-based Medical Image Analysis

Neuro Image Analysis

Projects

[Imaging Dementia: Brain Matters]

Publications

Conference Papers

Bortsova G., Dubost F., Orting S., Katramados I., Hogeweg L., Thomsen L., Wille M., de Bruijne M. Deep Learning from Label Proportions for Emphysema Quantification. MICCAI 2018 Marques F., Dubost F., Kemner-van de Corput M., Tiddens H. A. W. , de Bruijne. M. Quantification of lung abnormalities in cystic fibrosis using deep networks. SPIE Medical Imaging 2018 Dubost, F., Bortsova, G., Adams, H., Ikram, M.A., Niessen, W.J., Vernooij, M. and De Bruijne, M. GP-Unet: Lesion detection from weak labels with a 3D regression network. MICCAI 2017 Bortsova, G., van Tulder, G., Dubost, F., Peng, T., Navab, N., van der Lugt, A., Bos, D. and De Bruijne, M. Segmentation of intracranial arterial calcification with deeply supervised residual dropout networks. MICCAI 2017 Dubost, F., Peter, L., Rupprecht, C., Becker, B.G. and Navab, N. Hands-Free Segmentation of Medical Volumes via Binary Inputs. In Deep Learning and Data Labeling for Medical Applications, MICCAI 2016 workshop.

Conference Abstracts

Dubost, F., Adams, H., Bortsova, G., Ikram, M.A., Niessen, W.J., Vernooij, M. and De Bruijne, M. Automatic quantification of enlarged perivascular spaces on brain MRI. ECR 2018 Bortsova, G., van Tulder, G., Dubost, F., van der Lugt, A., Bos, D. and De Bruijne, M. Automatic detection of intracranial calcifications in non-contrast CT. ECR 2018 Bortsova G. , Ørting S.N. , Dubost F. , Katramados I., Hogeweg L., Wille M.M., Thomsen L.H. Automatic prediction of emphysema extent in low-dose CT by deep learning. ECR 2018