| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2067 | 2018 |
| MR brain image segmentation using an enhanced fuzzy c-means algorithm L Szilagyi, Z Benyo, SM Szilágyi, HS Adam Proceedings of the 25th annual international conference of the IEEE …, 2003 | 683 | 2003 |
| A large-scale assessment of hand hygiene quality and the effectiveness of the “WHO 6-steps” L Szilágyi, T Haidegger, Á Lehotsky, M Nagy, EA Csonka, X Sun, KL Ooi, ... BMC infectious diseases 13, 1-10, 2013 | 104 | 2013 |
| Detection of pneumonia using convolutional neural networks and deep learning P Szepesi, L Szilágyi Biocybernetics and biomedical engineering 42 (3), 1012-1022, 2022 | 86 | 2022 |
| Brain tumor segmentation with optimized random forest L Lefkovits, S Lefkovits, L Szilágyi Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2016 | 80 | 2016 |
| Automatic brain tumor segmentation in multispectral MRI volumes using a fuzzy c-means cascade algorithm L Szilagyi, L Lefkovits, B Benyo 2015 12th international conference on fuzzy systems and knowledge discovery …, 2015 | 61 | 2015 |
| Wavelet transform and neural-network-based adaptive filtering for QRS detection SM Szilagyi, L Szilagyi Proceedings of the 22nd annual international conference of the IEEE …, 2000 | 54 | 2000 |
| A modified fuzzy c-means algorithm for MR brain image segmentation L Szilágyi, SM Szilágyi, Z Benyó Image Analysis and Recognition: 4th International Conference, ICIAR 2007 …, 2007 | 53 | 2007 |
| Comparison between neural-network-based adaptive filtering and wavelet transform for ECG characteristic points detection SM Szildgyi, L Szildgyi, L David Proceedings of the 19th Annual International Conference of the IEEE …, 1997 | 46 | 1997 |
| Efficient inhomogeneity compensation using fuzzy c-means clustering models L Szilágyi, SM Szilágyi, B Benyó Computer methods and programs in biomedicine 108 (1), 80-89, 2012 | 45 | 2012 |
| Quantitative impact of direct, personal feedback on hand hygiene technique A Lehotsky, L Szilágyi, T Ferenci, L Kovács, R Pethes, G Wéber, ... Journal of Hospital Infection 91 (1), 81-84, 2015 | 44 | 2015 |
| Intensity inhomogeneity compensation and segmentation of MR brain images using hybrid c-means clustering models L Szilágyi, SM Szilágyi, B Benyó, Z Benyó Biomedical signal processing and control 6 (1), 3-12, 2011 | 44 | 2011 |
| Generalization rules for the suppressed fuzzy c-means clustering algorithm L Szilágyi, SM Szilágyi Neurocomputing 139, 298-309, 2014 | 36 | 2014 |
| Towards objective hand hygiene technique assessment: validation of the ultraviolet-dye-based hand-rubbing quality assessment procedure Á Lehotsky, L Szilágyi, S Bánsághi, P Szerémy, G Wéber, T Haidegger Journal of Hospital Infection 97 (1), 26-29, 2017 | 34 | 2017 |
| Fuzzy-Possibilistic Product Partition: A Novel Robust Approach to c-Means Clustering L Szilágyi Modeling Decision for Artificial Intelligence: 8th International Conference …, 2011 | 31 | 2011 |
| A new method for epileptic waveform recognition using wavelet decomposition and artificial neural networks L Szilagnyi, Z Benyó, SM Szilágyi Proceedings of the Second Joint 24th Annual Conference and the Annual Fall …, 2002 | 31 | 2002 |
| Adaptive wavelet-transform-based ECG waveforms detection SM Szilagyi, Z Benyo, L Szilagyi, L David Proceedings of the 25th Annual International Conference of the IEEE …, 2003 | 29 | 2003 |
| A fully automatic procedure for brain tumor segmentation from multi-spectral MRI records using ensemble learning and atlas-based data enhancement Á Győrfi, L Szilágyi, L Kovács Applied Sciences 11 (2), 564, 2021 | 28 | 2021 |
| Analytical and numerical evaluation of the suppressed fuzzy c-means algorithm: a study on the competition in c-means clustering models L Szilágyi, SM Szilágyi, Z Benyó Soft Computing 14, 495-505, 2010 | 28 | 2010 |
| Brain tumor segmentation and survival prediction using a cascade of random forests S Lefkovits, L Szilágyi, L Lefkovits International MICCAI Brainlesion Workshop, 334-345, 2018 | 27 | 2018 |
Levente KovácsProfessor, Obuda UniversityVerified email at nik.uni-obuda.hu
