Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Elmar W, Lang"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract In this study, an automated 2D machine learning approach for fast and precise segmentation of MS lesions from multi-modal magnetic resonance images (mmMRI) is presented. The method is based on an U-Net like convolutional neural network (CNN)
Externí odkaz:
https://doaj.org/article/e039b9ef344a4cee9a96bdf35b49fb5b
Publikováno v:
Applied Sciences, Vol 12, Iss 21, p 11184 (2022)
The success of the convolutional neural network (CNN) comes with a tremendous growth of diverse CNN structures, making it hard to deploy on limited-resource platforms. These over-sized models contain a large amount of filters in the convolutional lay
Externí odkaz:
https://doaj.org/article/20603cb9e4d742d6876ab86437d88232
Publikováno v:
Frontiers in Neuroscience, Vol 14 (2020)
Independent component analysis (ICA), being a data-driven method, has been shown to be a powerful tool for functional magnetic resonance imaging (fMRI) data analysis. One drawback of this multivariate approach is that it is not, in general, compatibl
Externí odkaz:
https://doaj.org/article/8fdedcaca2fe4049b48c32d96f983827
Publikováno v:
The Journal of Supercomputing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92b6010d07ef3c11a30c33942d9ebd41
https://doi.org/10.1007/s11227-023-05150-1
https://doi.org/10.1007/s11227-023-05150-1
Publikováno v:
Frontiers in Human Neuroscience, Vol 12 (2018)
Investigating temporal variability of functional connectivity is an emerging field in connectomics. Entering dynamic functional connectivity by applying sliding window techniques on resting-state fMRI (rs-fMRI) time courses emerged from this topic. W
Externí odkaz:
https://doaj.org/article/a80f3559827c4fdf9a7e9b96c4bb671d
Publikováno v:
PLoS ONE, Vol 11, Iss 12, p e0167957 (2016)
Lately, Ensemble Empirical Mode Decomposition (EEMD) techniques receive growing interest in biomedical data analysis. Event-Related Modes (ERMs) represent features extracted by an EEMD from electroencephalographic (EEG) recordings. We present a new a
Externí odkaz:
https://doaj.org/article/64566607f9e742cd8c7d2243d687335b
Autor:
Karema Al-Subari, Saad Al-Baddai, Ana Maria Tomé, Gregor Volberg, Rainer Hammwöhner, Elmar W Lang
Publikováno v:
PLoS ONE, Vol 10, Iss 4, p e0119489 (2015)
We discuss a data-driven analysis of EEG data recorded during a combined EEG/fMRI study of visual processing during a contour integration task. The analysis is based on an ensemble empirical mode decomposition (EEMD) and discusses characteristic feat
Externí odkaz:
https://doaj.org/article/dd8a81a78bd24a8f94580d89b2810037
Autor:
Simon, Wein, Gustavo, Deco, Ana Maria, Tomé, Markus, Goldhacker, Wilhelm M, Malloni, Mark W, Greenlee, Elmar W, Lang
Publikováno v:
Computational Intelligence and Neuroscience
This short survey reviews the recent literature on the relationship between the brain structure and its functional dynamics. Imaging techniques such as diffusion tensor imaging (DTI) make it possible to reconstruct axonal fiber tracks and describe th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::120f3b05d5140e0fc563197e19713f8b
https://pubmed.ncbi.nlm.nih.gov/34135951
https://pubmed.ncbi.nlm.nih.gov/34135951
Autor:
Theresia I, Götz, Elmar W, Lang, Christian, Schmidkonz, Andreas, Maier, Torsten, Kuwert, Philipp, Ritt
Publikováno v:
Zeitschrift fur medizinische Physik. 30(2)
Currently, there is a high interest inWe applied a PF for de-noising the TACs of 26 patients, who underwentThe number of particles was set to 1000. Optimal values for noise of observations and noise of the model were 0.25 and 0.5, respectively. The d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::a794d2d51c05cb4e527963b706bb9b38
https://pubmed.ncbi.nlm.nih.gov/31859029
https://pubmed.ncbi.nlm.nih.gov/31859029
Autor:
Karema, Al-Subari, Saad, Al-Baddai, Ana Maria, Tomé, Gregor, Volberg, Rainer, Hammwöhner, Elmar W, Lang
Publikováno v:
PLoS ONE, Vol 10, Iss 4, p e0119489 (2015)
PLoS ONE
PLoS ONE
We discuss a data-driven analysis of EEG data recorded during a combined EEG/fMRI study of visual processing during a contour integration task. The analysis is based on an ensemble empirical mode decomposition (EEMD) and discusses characteristic feat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0f6d7b6744c9f92144c2d05b332f87f
