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Diana Maria Sima

Observed names: D M Sima, D. M. Sima, D. Sima, D.M. Sima, DM Sima, Diana M Sima, Diana M. Sima, Diana Sima, Sima, Diana, Sima, Diana M, Sima, Diana M.
Observed institutions: Vrije Universiteit Brussel, University of Antwerp, Vita-Salute San Raffaele University, Universitair Ziekenhuis Leuven, University Medical Center Utrecht, iMinds, University of Oxford, IMEC, Universitair Ziekenhuis Brussel, Icometrix (Belgium), Technical University of Denmark, KU Leuven
ORCID: 0000-0002-0118-2905
Observed ORCID: 0000-0002-0118-2905
OpenAlex ID: A5088038335
Longitudinal multiple sclerosis lesion segmentation: Resource and challenge
2017 · Aaron Carass, Snehashis Roy, et al. · NeuroImage · 357
Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images
2015 · Saurabh Jain, Diana M. Sima, et al. · NeuroImage Clinical · 220
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MRS signal quantitation: A review of time- and frequency-domain methods
2008 · Jean-Baptiste Poullet, Diana M. Sima, et al. · Journal of Magnetic Resonance · 153
An automated quantitation of short echo time MRS spectra in an open source software environment: AQSES
2006 · Jean‐Baptiste Poullet, Diana M. Sima, et al. · NMR in Biomedicine · 151
Regularized Total Least Squares Based on Quadratic Eigenvalue Problem Solvers
2004 · Diana M. Sima, Sabine Van Huffel, et al. · BIT Numerical Mathematics · 101
Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas
2014 · Sofie Van Cauter, Frederik De Keyzer, et al. · Neuro-Oncology · 80
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Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI
2016 · N. Sauwen, M. Acou, et al. · NeuroImage Clinical · 78
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Automatic Quantification of Computed Tomography Features in Acute Traumatic Brain Injury
2019 · Saurabh Jain, Thijs Vande Vyvere, et al. · Journal of Neurotrauma · 77
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Reliable measurements of brain atrophy in individual patients with multiple sclerosis
2016 · Dirk Smeets, Annemie Ribbens, et al. · Brain and Behavior · 74
Machine Learning Approach for Classifying Multiple Sclerosis Courses by Combining Clinical Data with Lesion Loads and Magnetic Resonance Metabolic Features
2017 · Adrian Ion-Mărgineanu, Gabriel Kocevar, et al. · Frontiers in Neuroscience · 63
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icobrain ms 5.1: Combining unsupervised and supervised approaches for improving the detection of multiple sclerosis lesions
2021 · Mladen Rakić, Sophie Vercruyssen, et al. · NeuroImage Clinical · 58
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Factorizer: A scalable interpretable approach to context modeling for medical image segmentation
2022 · Pooya Ashtari, Diana M. Sima, et al. · Medical Image Analysis · 57
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Measurement of Whole-Brain and Gray Matter Atrophy in Multiple Sclerosis: Assessment with MR Imaging
2018 · Loredana Storelli, Maria A. Rocca, et al. · Radiology · 57
Automated MRI volumetry as a diagnostic tool for Alzheimer's disease: Validation of icobrain dm
2020 · Hanne Struyfs, Diana Maria Sima, et al. · NeuroImage Clinical · 56
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Brain age as a surrogate marker for cognitive performance in multiple sclerosis
2022 · S Denissen, DA Engemann, et al. · European Journal of Neurology · 53
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Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization
2017 · Nicolas Sauwen, Marjan Acou, et al. · BMC Medical Imaging · 49
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Two Time Point MS Lesion Segmentation in Brain MRI: An Expectation-Maximization Framework
2016 · Saurabh Jain, Annemie Ribbens, et al. · Frontiers in Neuroscience · 44
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Hierarchical non‐negative matrix factorization (hNMF): a tissue pattern differentiation method for glioblastoma multiforme diagnosis using MRSI
2012 · Yuqian Li, Diana M. Sima, et al. · NMR in Biomedicine · 43
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Artificial Intelligence Assistive Software Tool for Automated Detection and Quantification of Amyloid-Related Imaging Abnormalities
2024 · Diana M. Sima, Thanh Vân Phan, et al. · JAMA Network Open · 42
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Inter- and Intra-Scanner Variability of Automated Brain Volumetry on Three Magnetic Resonance Imaging Systems in Alzheimer’s Disease and Controls
2021 · Mandy Melissa Jane Wittens, Gert-Jan Allemeersch, et al. · Frontiers in Aging Neuroscience · 39
Patch-Based Super-Resolution of MR Spectroscopic Images: Application to Multiple Sclerosis
2017 · Saurabh Jain, Diana M. Sima, et al. · Frontiers in Neuroscience · 38
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Separable nonlinear least squares fitting with linear bound constraints and its application in magnetic resonance spectroscopy data quantification
2006 · Diana M. Sima, Sabine Van Huffel · Journal of Computational and Applied Mathematics · 38
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High-resolution metabolic mapping of gliomas via patch-based super-resolution magnetic resonance spectroscopic imaging at 7T
2019 · Gilbert Hangel, Saurabh Jain, et al. · NeuroImage · 36
Motor cortex metabolite alterations in amyotrophic lateral sclerosis assessed in vivo using edited and non-edited magnetic resonance spectroscopy
2019 · A. Weerasekera, R. Peeters, et al. · Brain Research · 35
Sensorimotor cortex neurometabolite levels as correlate of motor performance in normal aging: evidence from a 1H-MRS study
2019 · Oron Levin, Akila Weerasekera, et al. · NeuroImage · 34
Works count: 194
Citation count: 3,114
H-index: 30
I10-index: 65
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