| Automatic quality control in clinical 1H MRSI of brain cancer N Pedrosa de Barros, R McKinley, U Knecht, R Wiest, J Slotboom NMR in Biomedicine 29 (5), 563-575, 2016 | 43 | 2016 |
| Automated MRI volumetry as a diagnostic tool for Alzheimer's disease: Validation of icobrain dm H Struyfs, DM Sima, M Wittens, A Ribbens, NP de Barros, T Vân Phan, ... NeuroImage: Clinical 26, 102243, 2020 | 38 | 2020 |
| Quality management in in vivo proton MRS NP de Barros, J Slotboom Analytical biochemistry 529, 98-116, 2017 | 29 | 2017 |
| Quality of clinical brain tumor MR spectra judged by humans and machine learning tools SP Kyathanahally, V Mocioiu, N Pedrosa de Barros, J Slotboom, ... Magnetic resonance in medicine 79 (5), 2500-2510, 2018 | 27 | 2018 |
| Improving labeling efficiency in automatic quality control of MRSI data N Pedrosa de Barros, R McKinley, R Wiest, J Slotboom Magnetic resonance in medicine 78 (6), 2399-2405, 2017 | 22 | 2017 |
| MRI biomarkers for Alzheimer's disease: the impact of functional connectivity in the default mode network and structural connectivity between lobes on diagnostic accuracy R Mohtasib, J Alghamdi, A Jobeir, A Masawi, NP De Barros, T Billiet, ... Heliyon 8 (2), 2022 | 12 | 2022 |
| A contrast augmentation approach to improve multi-scanner generalization in MRI MI Meyer, E de la Rosa, N Pedrosa de Barros, R Paolella, K Van Leemput, ... Frontiers in neuroscience 15, 708196, 2021 | 10 | 2021 |
| Analysis of metabolic abnormalities in high‐grade glioma using MRSI and convex NMF N Pedrosa de Barros, R Meier, M Pletscher, S Stettler, U Knecht, M Reyes, ... NMR in Biomedicine 32 (8), e4109, 2019 | 10 | 2019 |
| Automatic quality assessment of short and long-TE brain tumour MRSI data using novel Spectral Features NM Pedrosa de Barros, U Knecht, R McKinley, J Giezendanner, R Wiest, ... ISMRM 2016, Singapore, 2016 | 7* | 2016 |
| On the relation between MR spectroscopy features and the distance to MRI‐visible solid tumor in GBM patients N Pedrosa de Barros, R Meier, M Pletscher, S Stettler, U Knecht, ... Magnetic resonance in medicine 80 (6), 2339-2355, 2018 | 6 | 2018 |
| A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases V Mocioiu, NMP De Barros, S Ortega Martorell, J Slotboom, U Knecht, ... ESANN 2016 proceedings: European Symposium on Artificial Neural Networks …, 2016 | 4 | 2016 |
| Comparison of different automatic solutions for resection cavity segmentation in postoperative MRI volumes including longitudinal acquisitions L Canalini, J Klein, NP de Barros, DM Sima, D Miller, H Hahn Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and …, 2021 | 2 | 2021 |
| Highlighting differences between GBM and brain metastasis using a blind source separation method applied to MRSI data NM Pedrosa de Barros, V Mocioiu, S Ortega Martorell, U Knecht, C Arús, ... ESMRMB 2015, Edinburgh, UK, 2015 | 2 | 2015 |
| Analysis of structural and functional connectivity MRI biomarkers in Alzheimer’s disease: Neuroimaging/Multi‐modal comparisons D Smeets, NP de Barros, T Billiet, DM Sima, R Mohtasib, J Alghamdi, ... Alzheimer's & Dementia 16, e042891, 2020 | 1 | 2020 |
| Evaluation of spinal cord atrophy in different MS subtypes using icospine W Van Hecke, T Billiet, NP de Barros, D Sima, F Durand-Dubief, ... MULTIPLE SCLEROSIS JOURNAL 25, 339-340, 2019 | 1 | 2019 |
| Computer Aided Radiological Diagnostics: Random Forest Classification of Glioma Tumor Progression using Image Texture Parameters derived from ADC-Maps J Slotboom, NP de Barros, N Porz, U Knecht, P Schucht, E Hermann, ... Proceedings of the 23rd Annual Meeting of the ISMRM 2262, 2014 | 1 | 2014 |
| AI-based characterization of multiple sclerosis clinical symptomatology using lesion parenchymal fraction: empirical support for the topographical model of MS (P3-3.018) S Krieger, T Billiet, C Maes, N De Barros, W Van Hecke, A Ribbens, ... Neurology 100 (17 Supplement 2), 2023 | | 2023 |
| AI-based characterisation of multiple sclerosis clinical symptomatology using lesion parenchymal fraction: consistency with the topographical model of MS S Krieger, T Billiet, C Maes, A Chatterjee, N de Barros, W Van Hecke, ... MULTIPLE SCLEROSIS JOURNAL 28 (3_ SUPPL), 809-809, 2022 | | 2022 |
| Phenotype‐dependent relationships between cortical macro‐and micro‐structural neurodegeneration in frontotemporal lobar degeneration K Placek, V Anania, T Van Phan, NP de Barros, T Billiet, A Ribbens, ... Alzheimer's & Dementia 17, e051717, 2021 | | 2021 |
| Prediction of Tumor Progression Time Interval in Malignant Glioma Using Textural Information derived from FLAIR and T1c MR-images and Machine Learning J Slotboom, U Knecht, NP de Barros, T Nannen, M Zbinden, E Hewer, ... Proc. Intl. Soc. Mag. Reson. Med 26, 0896, 2018 | | 2018 |
