Підписатись
Alexandra de Sitter
Alexandra de Sitter
Невідома організація
Підтверджена електронна адреса в vumc.nl
Назва
Посилання
Посилання
Рік
Urgent challenges in quantification and interpretation of brain grey matter atrophy in individual MS patients using MRI
H Amiri, A de Sitter, K Bendfeldt, M Battaglini, CAMG Wheeler-Kingshott, ...
NeuroImage: Clinical 19, 466-475, 2018
602018
Agreement of MSmetrix with established methods for measuring cross-sectional and longitudinal brain atrophy
MD Steenwijk, H Amiri, MM Schoonheim, A De Sitter, F Barkhof, ...
NeuroImage: Clinical 15, 843-853, 2017
452017
Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study
A de Sitter, MD Steenwijk, A Ruet, A Versteeg, Y Liu, RA van Schijndel, ...
NeuroImage 163, 106-114, 2017
372017
Facing privacy in neuroimaging: Removing facial features degrades performance of image analysis methods
A de Sitter, M Visser, I Brouwer, KS Cover, RA van Schijndel, RS Eijgelaar, ...
European Radiology, 2019
342019
Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study
J Burggraaff, Y Liu, JC Prieto, J Simoes, A de Sitter, S Ruggieri, I Brouwer, ...
NeuroImage: Clinical 29, 102549, 2021
222021
Do mathematical model studies settle the controversy on the origin of cardiac synchronous trans-thoracic electrical impedance variations? A systematic review
A de Sitter, RM Verdaasdonk, TJC Faes
Physiological measurement 37 (9), R88, 2016
172016
Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort
A de Sitter, T Verhoeven, J Burggraaff, Y Liu, J Simoes, S Ruggieri, ...
Journal of neurology 267 (12), 3541-3554, 2020
142020
Opportunities for understanding MS mechanisms and progression with MRI using large-scale data sharing and artificial intelligence
H Vrenken, M Jenkinson, DL Pham, CRG Guttmann, D Pareto, ...
Neurology 97 (21), 989-999, 2021
102021
Development and evaluation of a manual segmentation protocol for deep grey matter in multiple sclerosis: Towards accelerated semi-automated references
A de Sitter, J Burggraaff, F Bartel, M Palotai, Y Liu, J Simoes, S Ruggieri, ...
NeuroImage: Clinical 30, 102659, 2021
32021
Consistency checks for partial volume correction of ASL perfusion maps
JP Kuijer, A De Sitter, MA Binnewijzend, F Barkhof, RM Verdaasdonk
Proc Intl Soc Mag Reson Med, 0
3
A distributed platform for making large scale manual reference datasets for MS lesion segmentation
S Damangir, A de Sitter, I Brouwer, CRG Guttmann, D Pareto, A Rovira, ...
MULTIPLE SCLEROSIS JOURNAL 24, 864-864, 2018
12018
Impact of removing facial features from MR images of MS patients on automatic lesion and atrophy metrics
A de Sitter, M Visser, I Brouwer, RA van Schijndel, BMJ Uitdehaag, ...
MULTIPLE SCLEROSIS JOURNAL 23, 226-226, 2017
12017
MS-specific deep learning segmentation of deep gray matter
K Koopman, I Brouwer, N Cantavella, A de Sitter, F Barkhof, H Vrenken
MULTIPLE SCLEROSIS JOURNAL 27 (2_ SUPPL), 449-449, 2021
2021
Creating accurate reference segmentations of deep GM structures in MS patients by fast semi-automated outlining
A de Sitter, F Bartel, M Palotai, J Burggraaff, Y Liu, J Simoes, S Ruggieri, ...
MULTIPLE SCLEROSIS JOURNAL 24, 620-622, 2018
2018
Lesion simulation software LESIM: a robust and flexible tool for realistic simulation of white matter lesions
MM Weeda, A de Sitter, I Brouwer, MM de Boer, RJ van Tuijl, ...
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Статті 1–15