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Diana Maria Sima
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2020 – today
- 2024
- [i10]Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew, Alexandre Hutton, Roland Wiest, Johannes Kaesmacher, Uta Hanning, Arsany Hakim, Richard Zubal, Waldo Valenzuela, David Robben, Diana Maria Sima, Vincenzo Anania, Arne Brys, James A. Meakin, Anne Mickan, Gabriel Broocks, Christian Heitkamp, Shengbo Gao, Kongming Liang, Ziji Zhang, Md Mahfuzur Rahman Siddiquee, Andriy Myronenko, Pooya Ashtari, Sabine Van Huffel, Hyun-su Jeong, Chiho Yoon, Chulhong Kim, Jiayu Huo, Sébastien Ourselin, Rachel Sparks, Albert Clèrigues, Arnau Oliver, Xavier Lladó, Liam F. Chalcroft, Ioannis Pappas, Jeroen Bertels, Ewout Heylen, Juliette Moreau, Nima Hatami, Carole Frindel, Abdul Qayyum, Moona Mazher, Domenec Puig, Shao-Chieh Lin, Chun-Jung Juan, Tianxi Hu, Lyndon Boone, Maged Goubran
, Yi-Jui Liu, Susanne Wegener, Florian Kofler, Ivan Ezhov, Suprosanna Shit, Moritz Roman Hernandez Petzsche, Bjoern H. Menze, Jan S. Kirschke, Benedikt Wiestler:
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge. CoRR abs/2403.19425 (2024) - 2023
- [j14]Pooya Ashtari
Factorizer: A scalable interpretable approach to context modeling for medical image segmentation. Medical Image Anal. 84: 102706 (2023) - 2022
- [c22]Jana Vujadinovic, Jaime Simarro Viana
Knowledge-Guided Segmentation of Isointense Infant Brain. PIPPI@MICCAI 2022: 105-114 - [i9]Pooya Ashtari, Diana Maria Sima, Lieven De Lathauwer, Dominique Sappey-Marinier, Frederik Maes, Sabine Van Huffel:
Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image Segmentation. CoRR abs/2202.12295 (2022) - [i8]Luca Canalini, Jan Klein, Nuno Pedrosa de Barros, Diana Maria Sima, Dorothea Miller, Horst K. Hahn:
Comparison of different automatic solutions for resection cavity segmentation in postoperative MRI volumes including longitudinal acquisitions. CoRR abs/2210.07806 (2022) - 2021
- [j13]Ezequiel de la Rosa, Diana Maria Sima, Bjoern H. Menze
AIFNet: Automatic vascular function estimation for perfusion analysis using deep learning. Medical Image Anal. 74: 102211 (2021) - [c21]Maria Inês Meyer
An Augmentation Strategy to Mimic Multi-Scanner Variability in MRI. ISBI 2021: 1196-1200 - [c20]Luca Canalini, Jan Klein, Nuno Pedrosa de Barros, Diana Maria Sima, Dorothea Miller, Horst K. Hahn:
Comparison of different automatic solutions for resection cavity segmentation in postoperative MRI volumes including longitudinal acquisitions. Image-Guided Procedures 2021 - [i7]Maria Inês Meyer, Ezequiel de la Rosa, Nuno Pedrosa de Barros, Roberto Paolella, Koen Van Leemput, Diana Maria Sima:
An augmentation strategy to mimic multi-scanner variability in MRI. CoRR abs/2103.12595 (2021) - [i6]Ezequiel de la Rosa, David Robben, Diana Maria Sima, Jan S. Kirschke, Bjoern H. Menze:
Differentiable Deconvolution for Improved Stroke Perfusion Analysis. CoRR abs/2103.17111 (2021) - 2020
- [c19]Jaime Simarro Viana
Unsupervised 3D Brain Anomaly Detection. BrainLes@MICCAI (1) 2020: 133-142 - [c18]Ezequiel de la Rosa, David Robben, Diana Maria Sima
Differentiable Deconvolution for Improved Stroke Perfusion Analysis. MICCAI (7) 2020: 593-602 - [i5]Mattias Billast
Improved inter-scanner MS lesion segmentation by adversarial training on longitudinal data. CoRR abs/2002.00952 (2020) - [i4]Ezequiel de la Rosa, Diana Maria Sima, Bjoern H. Menze, Jan S. Kirschke, David Robben:
AIFNet: Automatic Vascular Function Estimation for Perfusion Analysis Using Deep Learning. CoRR abs/2010.01617 (2020) - [i3]Jaime Simarro Viana, Ezequiel de la Rosa, Thijs Vande Vyvere, David Robben, Diana Maria Sima:
Unsupervised 3D Brain Anomaly Detection. CoRR abs/2010.04717 (2020)
2010 – 2019
- 2019
- [j12]Gilbert Hangel
High-resolution metabolic mapping of gliomas via patch-based super-resolution magnetic resonance spectroscopic imaging at 7T. NeuroImage 191: 587-595 (2019) - [j11]Oron Levin
Sensorimotor cortex neurometabolite levels as correlate of motor performance in normal aging: evidence from a 1H-MRS study. NeuroImage 202 (2019) - [j10]Halandur Nagaraja Bharath
Tensor-Based Method for Residual Water Suppression in $^1$H Magnetic Resonance Spectroscopic Imaging. IEEE Trans. Biomed. Eng. 66(2): 584-594 (2019) - [c17]Mattias Billast
Improved Inter-scanner MS Lesion Segmentation by Adversarial Training on Longitudinal Data. BrainLes@MICCAI (1) 2019: 98-107 - [c16]Ezequiel de la Rosa, Diana Maria Sima
A Radiomics Approach to Traumatic Brain Injury Prediction in CT Scans. ISBI 2019: 732-735 - [c15]Maria Inês Meyer
Relevance Vector Machines for Harmonization of MRI Brain Volumes Using Image Descriptors. OR/MLCN@MICCAI 2019: 77-85 - [i2]Maria Inês Meyer, Ezequiel de la Rosa, Koen Van Leemput, Diana Maria Sima:
Relevance Vector Machines for harmonization of MRI brain volumes using image descriptors. CoRR abs/1911.04289 (2019) - 2018
- [i1]Ezequiel de la Rosa, Diana Maria Sima, Thijs Vande Vyvere, Jan S. Kirschke, Bjoern H. Menze:
A Radiomics Approach to Traumatic Brain Injury Prediction in CT Scans. CoRR abs/1811.05699 (2018) - 2017
- [j9]Nicolas Sauwen, Marjan Acou, Diana Maria Sima
Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization. BMC Medical Imaging 17(1): 29:1-29:14 (2017) - [j8]Yuqian Li, Xin Liu, Feng Wei, Diana Maria Sima
An advanced MRI and MRSI data fusion scheme for enhancing unsupervised brain tumor differentiation. Comput. Biol. Medicine 81: 121-129 (2017) - [j7]Halandur Nagaraja Bharath
Nonnegative Canonical Polyadic Decomposition for Tissue-Type Differentiation in Gliomas. IEEE J. Biomed. Health Informatics 21(4): 1124-1132 (2017) - [c14]Adrian Ion-Margineanu, Sofie Van Cauter, Diana Maria Sima, Frederik Maes, Stefan Sunaert, Uwe Himmelreich, Sabine Van Huffel:
Comparison of manual and semi-manual delineations for classifying glioblastoma multiforme patients based on histogram and texture MRI features. ESANN 2017 - [c13]Adrian Ion-Margineanu, Gabriel Kocevar, Claudio Stamile, Diana Maria Sima
A Comparison of Machine Learning Approaches for Classifying Multiple Sclerosis Courses Using MRSI and Brain Segmentations. ICANN (2) 2017: 643-651 - [c12]Halandur Nagaraja Bharath
Tumor Segmentation from Multimodal MRI Using Random Forest with Superpixel and Tensor Based Feature Extraction. BrainLes@MICCAI 2017: 463-473 - 2016
- [j6]Iveta Hnetynková
Solvability of the Core Problem with Multiple Right-Hand Sides in the TLS Sense. SIAM J. Matrix Anal. Appl. 37(3): 861-876 (2016) - [c11]Nicolas Sauwen, Marjan Acou, Halandur Nagaraja Bharath, Diana Maria Sima, Jelle Veraart, Frederik Maes, Uwe Himmelreich, Eric Achten, Sabine Van Huffel:
Initializing nonnegative matrix factorization using the successive projection algorithm for multi-parametric medical image segmentation. ESANN 2016 - [c10]Halandur Nagaraja Bharath
Canonical polyadic decomposition for tissue type differentiation using multi-parametric MRI in high-grade gliomas. EUSIPCO 2016: 547-551 - [c9]Saurabh Jain, Diana Maria Sima
Patch based super-resolution of MR spectroscopic images. ISBI 2016: 452-456 - [c8]Saurabh Jain, Annemie Ribbens, Diana Maria Sima, Sabine Van Huffel, Frederik Maes
Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation. MCV/BAMBI@MICCAI 2016: 208-219 - [c7]Nicolas Sauwen, Diana Maria Sima
A Semi-Automated Segmentation Framework for MRI Based Brain Tumor Segmentation Using Regularized Nonnegative Matrix Factorization. SITIS 2016: 88-95 - 2015
- [j5]Yuqian Li, Diana Maria Sima
Corrections to "Unsupervised Nosologic Imaging for Glioma Diagnosis". IEEE Trans. Biomed. Eng. 62(8): 2091 (2015) - [c6]Halandur Nagaraja Bharath
Tensor based tumor tissue type differentiation using magnetic resonance spectroscopic imaging. EMBC 2015: 7003-7006 - 2013
- [j4]Yuqian Li, Diana Maria Sima
Unsupervised Nosologic Imaging for Glioma Diagnosis. IEEE Trans. Biomed. Eng. 60(6): 1760-1763 (2013) - 2012
- [c5]Yuqian Li, Diana Maria Sima, Sofie Van Cauter, Uwe Himmelreich, Yiming Pi, Sabine Van Huffel:
Tissue Type Differentiation for Brain Glioma using Non-negative Matrix Factorization. BIOSIGNALS 2012: 25-31 - [c4]Yuqian Li, Diana Maria Sima, Sofie Van Cauter, Uwe Himmelreich, Yiming Pi, Sabine Van Huffel:
Simulation Study of Tissue Type Differentiation using Non-negative Matrix Factorization. BIOSIGNALS 2012: 212-217 - 2011
- [j3]Iveta Hnetynková
The Total Least Squares Problem in AX ≈ B: A New Classification with the Relationship to the Classical Works. SIAM J. Matrix Anal. Appl. 32(3): 748-770 (2011) - [c3]M. I. Osorio Garcia, Diana Maria Sima, Sabine Van Huffel, F. U. Nielsen, Uwe Himmelreich:
Damping Factor Constraints and Metabolite Profile Selection Influence Magnetic Resonance Spectroscopy Data Quantification. BIOSIGNALS 2011: 176-181
2000 – 2009
- 2007
- [j2]Diana Maria Sima
Level choice in truncated total least squares. Comput. Stat. Data Anal. 52(2): 1103-1118 (2007) - 2006
- [j1]Diana Maria Sima, Sabine Van Huffel:
A class of template splines. Comput. Stat. Data Anal. 50(12): 3486-3499 (2006) - [c2]Andy Devos
Model order selection for quantification of a multi-exponential magnetic resonance spectrum. EMBC 2006: 1299-1302 - [c1]Jean-Baptiste Poullet, Diana Maria Sima
Frequency-selective quantification of short-echo time Magnetic Resonance spectra. EMBC 2006: 6351-6355
Coauthor Index
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last updated on 2024-11-28 21:25 CET by the dblp team
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