TitleAuthorsJournalDateLink to article
3D regression neural network for the quantification of enlarged perivascular spaces in brain MRIDubost, F., Adams, H., Bortsova, G., Ikram, M.A., Niessen, W., Vernooij, M. and de Bruijne, M.Medical Image Analysis2019
Enlarged perivascular spaces in brain MRI: Automated quantification in four regionsDubost, F., Yilmaz, P., Adams, H., Bortsova, G., Ikram, M.A., Niessen, W., Vernooij, M. and de Bruijne, M.NeuroImage2019


TitleAuthorsConferenceDateLink to article
Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of DementiaVenkatraghavan, V.*, Dubost, F.*, Bron, E.E., Niessen, W.J., de Bruijne, M. and Klein, S.IPMI2019
Deep learning from label proportions for emphysema quantificationBortsova, G., Dubost, F., Ørting, S., Katramados, I., Hogeweg, L., Thomsen, L., Wille, M. and de Bruijne, M.MICCAI2018
Quantification of lung abnormalities in cystic fibrosis using deep networksMarques, F., Dubost, F., Kemner-van de Corput, M., Tiddens, H.A. and de Bruijne, M.SPIE2018
GP-Unet: Lesion Detection from Weak Labelswith a 3D Regression NetworkDubost, F., Bortsova, G., Adams, H., Ikram, A., Niessen, W.J., Vernooij, M. and De Bruijne, M.MICCAI2017
Segmentation of intracranial arterial calcification with deeply supervised residual dropout networksBortsova, G., van Tulder, G., Dubost, F., Peng, T., Navab, N., van der Lugt, A., Bos, D. and De Bruijne, M.MICCAI2017
Hands-free segmentation of medical volumes via binary inputsDubost, F., Peter, L., Rupprecht, C., Becker, B.G. and Navab, N.MICCAI Workshop2016