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المؤلفون: Oula Puonti, Agnes Flöel, Axel Thielscher, Ulrike Grittner, Daria Antonenko
المصدر: Antonenko, D, Grittner, U, Puonti, O, Flöel, A & Thielscher, A 2021, ' Estimation of individually induced e-field strength during transcranial electric stimulation using the head circumference ', Brain Stimulation, vol. 14, no. 5, pp. 1055-1058 . https://doi.org/10.1016/j.brs.2021.07.001Test
Brain stimulation 14(5), 1055-1058 (2021). doi:10.1016/j.brs.2021.07.001
Brain Stimul
Brain Stimulation, Vol 14, Iss 5, Pp 1055-1058 (2021)مصطلحات موضوعية: Adult, Electric field simulation, Biophysics, Context (language use), Neurosciences. Biological psychiatry. Neuropsychiatry, Transcranial Direct Current Stimulation, Article, Brain anatomy, Mathematical equations, Electricity, Electric field, medicine, Humans, Individualization, ddc:610, Non-invasive brain stimulation, diagnostic imaging [Brain], Electric stimulation, Physics, medicine.diagnostic_test, General Neuroscience, Brain, Magnetic resonance imaging, Magnetic Resonance Imaging, Transcranial Magnetic Stimulation, Electric Stimulation, Head circumference, Computational modelling, Neurology (clinical), Head, Biomedical engineering, RC321-571, Transcranial electrical stimulation
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c97251517f3090563fcd9701d2c63b4aTest
https://orbit.dtu.dk/en/publications/734e9669-0c90-40f3-8d21-4a616cc0afc4Test -
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المؤلفون: Hasan H. Eroglu, Oula Puonti, Lars G. Hanson, Hartwig R. Siebner, Fróði Gregersen, Cihan Göksu, Axel Thielscher
المصدر: NeuroImage, Vol 243, Iss, Pp 118517-(2021)
NeuroImage
Eroğlu, H H, Puonti, O, Göksu, C, Gregersen, F, Siebner, H R, Hanson, L G & Thielscher, A 2021, ' On the reconstruction of magnetic resonance current density images of the human brain : Pitfalls and perspectives ', NeuroImage, vol. 243, 118517 . https://doi.org/10.1016/j.neuroimage.2021.118517Testمصطلحات موضوعية: Scanner, Projected current density algorithm, Computer science, Cognitive Neuroscience, Hierarchical model selection, Neurosciences. Biological psychiatry. Neuropsychiatry, Signal-To-Noise Ratio, Current density imaging, Transcranial Direct Current Stimulation, Field (computer science), Magnetic resonance electrical impedance imaging, Data acquisition, Electric Impedance, Image Processing, Computer-Assisted, Humans, Computer Simulation, Statistical hypothesis testing, Ground truth, Brain, Magnetic Resonance Imaging, Magnetic resonance current density imaging, Neurology, Current (fluid), Current density, Algorithm, Algorithms, Volume (compression), RC321-571
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51c39c20cdbd484e0b6c993bcffce2a9Test
https://doi.org/10.1016/j.neuroimage.2021.118517Test -
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المؤلفون: Stefano Cerri, Hartwig R. Siebner, Jens Wuerfel, Mark Mühlau, Oula Puonti, Koen Van Leemput, Dominik Meier
المصدر: Cerri, S, Puonti, O, Meier, D S, Wuerfel, J, Mühlau, M, Siebner, H R & Van Leemput, K 2020, ' A Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis ', NeuroImage, vol. 225, 117471 . https://doi.org/10.1016/j.neuroimage.2020.117471Test
NeuroImage, Vol 225, Iss, Pp 117471-(2021)
NeuroImage
Cerri, S, Puonti, O, Meier, D S, Wuerfel, J, Mühlau, M, Siebner, H R & Van Leemput, K 2021, ' A contrast-adaptive method for simultaneous whole-brain and lesion segmentation in multiple sclerosis ', NeuroImage, vol. 225, 117471 . https://doi.org/10.1016/j.neuroimage.2020.117471Testمصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer science, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Quantitative Methods, Machine Learning (cs.LG), 0302 clinical medicine, Image Processing, Computer-Assisted, Contrast (vision), Segmentation, Gray Matter, Quantitative Methods (q-bio.QM), media_common, Lesion segmentation, Image and Video Processing (eess.IV), 05 social sciences, Brain, Magnetic Resonance Imaging, White Matter, ddc, Generative model, Neurology, Algorithms, Adaptive method, Cognitive Neuroscience, media_common.quotation_subject, White matter lesion, Neuroimaging, 050105 experimental psychology, Article, lcsh:RC321-571, Multiple sclerosis, 03 medical and health sciences, Image Interpretation, Computer-Assisted, FOS: Electrical engineering, electronic engineering, information engineering, medicine, Humans, 0501 psychology and cognitive sciences, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Whole-brain segmentation, business.industry, Pattern recognition, Electrical Engineering and Systems Science - Image and Video Processing, medicine.disease, Hyperintensity, FOS: Biological sciences, Artificial intelligence, Atrophy, business, 030217 neurology & neurosurgery
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c1db72ad48a733bc80cad2d60a5d7ffTest
http://arxiv.org/abs/2005.05135Test -
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المؤلفون: Kristoffer Hougaard Madsen, Koen Van Leemput, Hartwig R. Siebner, Axel Thielscher, Guilherme B. Saturnino, Oula Puonti
المصدر: Puonti, O, Van Leemput, K, Saturnino, G B, Siebner, H R, Madsen, K H & Thielscher, A 2020, ' Accurate and robust whole-head segmentation from magnetic resonance images for individualized head modeling ', NeuroImage, vol. 219, 117044 . https://doi.org/10.1016/j.neuroimage.2020.117044Test
NeuroImage
Science Direct-Neuroimage
NeuroImage, Vol 219, Iss, Pp 117044-(2020)مصطلحات موضوعية: Computer science, Cognitive Neuroscience, Electroencephalography, Transcranial Direct Current Stimulation, Article, 050105 experimental psychology, lcsh:RC321-571, 03 medical and health sciences, 0302 clinical medicine, Volume conductor modeling, Image Processing, Computer-Assisted, medicine, Humans, Computer Simulation, 0501 psychology and cognitive sciences, Segmentation, Non-invasive brain stimulation, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Brain Mapping, medicine.diagnostic_test, business.industry, 05 social sciences, Brain, Magnetoencephalography, Magnetic resonance imaging, Pattern recognition, Human brain, Magnetic Resonance Imaging, Transcranial Magnetic Stimulation, medicine.anatomical_structure, Neurology, Electromagnetic coil, Brain stimulation, Head segmentation, Artificial intelligence, business, Head, 030217 neurology & neurosurgery, MRI
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6d3c71646065cb22be137a37a4542fcTest
https://curis.ku.dk/portal/da/publications/accurate-and-robust-wholehead-segmentation-from-magnetic-resonance-images-for-individualized-head-modelingTest(6eeeafae-e1dc-4ad0-a561-ef3195617d43).html -
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المؤلفون: Juan Eugenio Iglesias, Koen Van Leemput, Oula Puonti
المصدر: Addi. Archivo Digital para la Docencia y la Investigación
instname
NeuroImage
Neuroimage
Puonti, O, Iglesias, J E & Van Leemput, K 2016, ' Fast and Sequence-Adaptive Whole-Brain Segmentation Using Parametric Bayesian Modeling ', NeuroImage, vol. 143, pp. 235–249 . https://doi.org/10.1016/j.neuroimage.2016.09.011Testمصطلحات موضوعية: Adult, Computer science, Cognitive Neuroscience, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Parametric models, Datasets as Topic, Scale-space segmentation, COGNITIVE NEUROSCIENCE, Bayesian inference, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Segmentation, Image Processing, Computer-Assisted, medicine, Humans, Brain segmentation, Computer vision, NEUROLOGY, Parametric statistics, Models, Statistical, medicine.diagnostic_test, business.industry, Segmentation-based object categorization, Brain, Bayes Theorem, Magnetic resonance imaging, Atlases, Magnetic Resonance Imaging, Bayesian modeling, Neurology, Feature (computer vision), Artificial intelligence, business, 030217 neurology & neurosurgery, MRI
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fda2358f28dfcd6173217c63c91d8b12Test
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المصدر: Puonti, O, Saturnino, G B, Madsen, K H & Thielscher, A 2020, ' Value and limitations of intracranial recordings for validating electric field modeling for transcranial brain stimulation ', NeuroImage, vol. 208, 116431 . https://doi.org/10.1016/j.neuroimage.2019.116431Test
NeuroImage, Vol 208, Iss, Pp 116431-(2020)
NeuroImageمصطلحات موضوعية: Adult, Field (physics), Computer science, Cognitive Neuroscience, Neuroimaging, Validation Studies as Topic, Transcranial Direct Current Stimulation, Brain mapping, 050105 experimental psychology, lcsh:RC321-571, TDCS, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, medicine, Humans, 0501 psychology and cognitive sciences, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, TACS, Errors-in-variables regression, medicine.diagnostic_test, 05 social sciences, Volume conductor model, Brain, Bayes Theorem, Magnetic resonance imaging, Magnetoencephalography, Models, Theoretical, medicine.disease, Magnetic Resonance Imaging, Bayesian regression, Neurology, Brain stimulation, Regression Analysis, Electrocorticography, Transcranial brain stimulation, Algorithm, 030217 neurology & neurosurgery
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::159b250a0f79773ee92d9245efc13fe0Test
https://doi.org/10.1016/j.neuroimage.2019.116431Test -
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المؤلفون: Jesper Duemose Nielsen, Kristoffer Hougaard Madsen, Axel Thielscher, Guilherme B. Saturnino, Oula Puonti, Camilla Gøbel Madsen, Christian Bauer, Hartwig R. Siebner
المصدر: Nielsen, J D, Madsen, K H, Puonti, O, Siebner, H R, Bauer, C, Madsen, C G, Saturnino, G B & Thielscher, A 2018, ' Automatic skull segmentation from MR images for realistic volume conductor models of the head: Assessment of the state-of-the-art ', NeuroImage, vol. 174, pp. 587-598 . https://doi.org/10.1016/j.neuroimage.2018.03.001Test
مصطلحات موضوعية: Adult, Male, Skull segmentation, Computer science, Cognitive Neuroscience, medicine.medical_treatment, Electroencephalography, Transcranial Direct Current Stimulation, Models, Biological, 030218 nuclear medicine & medical imaging, Pattern Recognition, Automated, 03 medical and health sciences, Young Adult, 0302 clinical medicine, medicine, Image Processing, Computer-Assisted, Humans, Segmentation, Computer vision, medicine.diagnostic_test, Human head, Transcranial direct-current stimulation, business.industry, Skull, Volume conductor model, Brain, Magnetoencephalography, Reproducibility of Results, Magnetic resonance imaging, Magnetic Resonance Imaging, medicine.anatomical_structure, Neurology, Brain stimulation, Female, Forward modeling, Artificial intelligence, Transcranial brain stimulation, business, 030217 neurology & neurosurgery, Software
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc641e9c17671ad6969c5c7e8b211ecfTest
https://pubmed.ncbi.nlm.nih.gov/29518567Test -
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المؤلفون: Oula Puonti, Juan Eugenio Iglesias, Koen Van Leemput
المصدر: ResearcherID
Advanced Information Systems Engineering ISBN: 9783642387081
MICCAI (1)مصطلحات موضوعية: Models, Anatomic, Computer science, Models, Neurological, Sensitivity and Specificity, Article, Pattern Recognition, Automated, Imaging, Three-Dimensional, Image Interpretation, Computer-Assisted, medicine, Humans, Segmentation, Computer vision, Computer Simulation, Observer Variation, Sequence, Models, Statistical, medicine.diagnostic_test, business.industry, Brain, Reproducibility of Results, Magnetic resonance imaging, Image Enhancement, Magnetic Resonance Imaging, Parametric model, Feasibility Studies, Artificial intelligence, business, Algorithms
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19d2279515c1f3c6122b1680c2c44123Test
https://pubmed.ncbi.nlm.nih.gov/24505732Test
