Journals

Title	Authors	Journal	Date	Link to article
3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI	Dubost, F., Adams, H., Bortsova, G., Ikram, M.A., Niessen, W., Vernooij, M. and de Bruijne, M.	Medical Image Analysis	2019	https://arxiv.org/pdf/1802.05914.pdf
Enlarged perivascular spaces in brain MRI: Automated quantification in four regions	Dubost, F., Yilmaz, P., Adams, H., Bortsova, G., Ikram, M.A., Niessen, W., Vernooij, M. and de Bruijne, M.	NeuroImage	2019	https://www.sciencedirect.com/science/article/pii/S1053811918319852

Conferences

Title	Authors	Conference	Date	Link to article
Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia	Venkatraghavan, V.*, Dubost, F.*, Bron, E.E., Niessen, W.J., de Bruijne, M. and Klein, S.	IPMI	2019	https://arxiv.org/pdf/1903.03386.pdf
Deep learning from label proportions for emphysema quantification	Bortsova, G., Dubost, F., Ørting, S., Katramados, I., Hogeweg, L., Thomsen, L., Wille, M. and de Bruijne, M.	MICCAI	2018	https://arxiv.org/pdf/1807.08601.pdf
Quantification of lung abnormalities in cystic fibrosis using deep networks	Marques, F., Dubost, F., Kemner-van de Corput, M., Tiddens, H.A. and de Bruijne, M.	SPIE	2018	https://arxiv.org/pdf/1803.07991.pdf
GP-Unet: Lesion Detection from Weak Labelswith a 3D Regression Network	Dubost, F., Bortsova, G., Adams, H., Ikram, A., Niessen, W.J., Vernooij, M. and De Bruijne, M.	MICCAI	2017	https://arxiv.org/pdf/1705.07999.pdf
Segmentation of intracranial arterial calcification with deeply supervised residual dropout networks	Bortsova, G., van Tulder, G., Dubost, F., Peng, T., Navab, N., van der Lugt, A., Bos, D. and De Bruijne, M.	MICCAI	2017	https://arxiv.org/pdf/1706.01148.pdf
Hands-free segmentation of medical volumes via binary inputs	Dubost, F., Peter, L., Rupprecht, C., Becker, B.G. and Navab, N.	MICCAI Workshop	2016	https://arxiv.org/pdf/1609.06192.pdf