Rachmadi, Muhammad FebrianValdés-Hernández, Maria Del CMakin, StephenWardlaw, JoannaKomura, Taku2020-07-082020-07-082020-07Rachmadi, M F, Valdés-Hernández, M D C, Makin, S, Wardlaw, J & Komura, T 2020, 'Automatic spatial estimation of white matter hyperintensities evolution in brain MRI using disease evolution predictor deep neural networks', Medical image analysis, vol. 63, 101712, pp. 101712. https://doi.org/10.1016/j.media.2020.101712ORCID: /0000-0001-8701-9043/work/76878021https://hdl.handle.net/2164/14679Funds from the Indonesia Endowment Fund for Education (LPDP), Ministry of Finance, Republic of Indonesia (MFR); Row Fogo Charitable Trust (Grant No. BRO-D.FID3668413)(MCVH); Wellcome Trust (patient recruitment, scanning, primary study Ref No. WT088134/Z/09/A); Fondation Leducq (Perivascular Spaces Transatlantic Network of Excellence); EU Horizon 2020 (SVDs@Target); and the MRC UK Dementia Research Institute at the University of Edinburgh (Wardlaw programme) are gratefully acknowledged. The Titan Xp used for this research was donated by the NVIDIA Corporation.195362370engWhite matter hyperintensities (WMH)WMH EvolutionDisease evolution predictor (DEP) modelsDEP Generative adversarial network (DEP-GAN)Small vessel disease (SVD)DEP U-Residual Network (DEP-UResNet)REGRESSIONSMALL VESSEL DISEASECOGNITIVE CONSEQUENCESRISK-FACTORSVOLUMEIMAGESDYNAMICSSTROKE LESION SEGMENTATIONPROGRESSIONINSIGHTSR MedicineRadiological and Ultrasound TechnologyHealth InformaticsRadiology Nuclear Medicine and imagingComputer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignRJournal article10.1016/j.media.2020.101712http://europepmc.org/abstract/med/32428823http://www.scopus.com/inward/record.url?scp=85084653087&partnerID=8YFLogxK63