László Szilágyi
László Szilágyi
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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
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
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), 1-10, 2013
Brain tumor segmentation with optimized random forest
L Lefkovits, S Lefkovits, L Szilágyi
International Workshop on Brainlesion: Glioma, Multiple Sclerosis, Stroke …, 2016
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
A modified fuzzy c-means algorithm for MR brain image segmentation
L Szilágyi, SM Szilágyi, Z Benyó
International Conference Image Analysis and Recognition, 866-877, 2007
Comparison between neural-network-based adaptive filtering and wavelet transform for ECG characteristic points detection
F Ng, F Mora, S Wong, G Passariello, D Almeida
Proceedings of the 19th Annual International Conference of the IEEE …, 1997
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
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
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
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
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
Generalization rules for the suppressed fuzzy c-means clustering algorithm
L Szilágyi, SM Szilágyi
Neurocomputing 139, 298-309, 2014
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 (5), 495-505, 2010
A modified FCM algorithm for fast segmentation of brain MR images
L Szilágyi, SM Szilágyi, Z Benyó
Analysis and Design of Intelligent Systems using Soft Computing Techniques …, 2007
On-line QRS complex detection using wavelet filtering
L Szilagyi, Z Benyo, SM Szilágyi, A Szlavecz, L Nagy
2001 Conference Proceedings of the 23rd Annual International Conference of …, 2001
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
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
Lessons to learn from a mistaken optimization
L Szilágyi
Pattern Recognition Letters 36, 29-35, 2014
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
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