Artículos de revistas sobre el tema "FMRI, motion, preprocessing, pipeline"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte los 35 mejores artículos de revistas para su investigación sobre el tema "FMRI, motion, preprocessing, pipeline".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Explore artículos de revistas sobre una amplia variedad de disciplinas y organice su bibliografía correctamente.
Kopal, Jakub, Anna Pidnebesna, David Tomeček, Jaroslav Tintěra y Jaroslav Hlinka. "Typicality of functional connectivity robustly captures motion artifacts in rs‐fMRI across datasets, atlases, and preprocessing pipelines". Human Brain Mapping 41, n.º 18 (2 de septiembre de 2020): 5325–40. http://dx.doi.org/10.1002/hbm.25195.
Texto completoChurchill, Nathan W., Anita Oder, Hervé Abdi, Fred Tam, Wayne Lee, Christopher Thomas, Jon E. Ween, Simon J. Graham y Stephen C. Strother. "Optimizing preprocessing and analysis pipelines for single-subject fMRI. I. Standard temporal motion and physiological noise correction methods". Human Brain Mapping 33, n.º 3 (31 de marzo de 2011): 609–27. http://dx.doi.org/10.1002/hbm.21238.
Texto completoMaximo, Jose, Frederic Briend, William Armstrong, Nina Kraguljac y Adrienne Lahti. "O2.2. EVALUATION OF THE RELATIONSHIP BETWEEN GLUTAMATE AND BRAIN CONNECTIVITY IN ANTIPSYCHOTIC-NAïVE FIRST EPISODE PATIENTS – A COMBINED MAGNETIC RESONANCE SPECTROSCOPY AND RESTING STATE FUNCTIONAL CONNECTIVITY MRI STUDY". Schizophrenia Bulletin 46, Supplement_1 (abril de 2020): S4. http://dx.doi.org/10.1093/schbul/sbaa028.007.
Texto completoJo, Hang Joon, Stephen J. Gotts, Richard C. Reynolds, Peter A. Bandettini, Alex Martin, Robert W. Cox y Ziad S. Saad. "Effective Preprocessing Procedures Virtually Eliminate Distance-Dependent Motion Artifacts in Resting State FMRI". Journal of Applied Mathematics 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/935154.
Texto completoNørgaard, Martin, Melanie Ganz, Claus Svarer, Vibe G. Frokjaer, Douglas N. Greve, Stephen C. Strother y Gitte M. Knudsen. "Different preprocessing strategies lead to different conclusions: A [11C]DASB-PET reproducibility study". Journal of Cerebral Blood Flow & Metabolism 40, n.º 9 (1 de octubre de 2019): 1902–11. http://dx.doi.org/10.1177/0271678x19880450.
Texto completoJaber, Hussain A., Hadeel K. Aljobouri, Ilyas Cankaya, Orhan M. Kocak y Oktay Algin. "Preparing fMRI Data for Postprocessing: Conversion Modalities, Preprocessing Pipeline, and Parametric and Nonparametric Approaches". IEEE Access 7 (2019): 122864–77. http://dx.doi.org/10.1109/access.2019.2937482.
Texto completoWang, Xian Lun, Li Li y Yu Xia Cui. "Detection and Location of Underwater Pipeline Based on Mathematical Morphology for an AUV". Key Engineering Materials 561 (julio de 2013): 591–96. http://dx.doi.org/10.4028/www.scientific.net/kem.561.591.
Texto completoFrew, Simon, Ahmad Samara, Hallee Shearer, Jeffrey Eilbott y Tamara Vanderwal. "Getting the nod: Pediatric head motion in a transdiagnostic sample during movie- and resting-state fMRI". PLOS ONE 17, n.º 4 (14 de abril de 2022): e0265112. http://dx.doi.org/10.1371/journal.pone.0265112.
Texto completoEldefrawy, Mahmoud, Scott A. King y Michael Starek. "Partial Scene Reconstruction for Close Range Photogrammetry Using Deep Learning Pipeline for Region Masking". Remote Sensing 14, n.º 13 (3 de julio de 2022): 3199. http://dx.doi.org/10.3390/rs14133199.
Texto completoAkdeniz, Gülsüm. "Complexity Analysis of Resting-State fMRI in Adult Patients with Attention Deficit Hyperactivity Disorder: Brain Entropy". Computational Intelligence and Neuroscience 2017 (2017): 1–6. http://dx.doi.org/10.1155/2017/3091815.
Texto completoBaxter, Luke, Sean Fitzgibbon, Fiona Moultrie, Sezgi Goksan, Mark Jenkinson, Stephen Smith, Jesper Andersson, Eugene Duff y Rebeccah Slater. "Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants". NeuroImage 186 (febrero de 2019): 286–300. http://dx.doi.org/10.1016/j.neuroimage.2018.11.006.
Texto completoXiao, Shunfu, Honghong Chai, Ke Shao, Mengyuan Shen, Qing Wang, Ruili Wang, Yang Sui y Yuntao Ma. "Image-Based Dynamic Quantification of Aboveground Structure of Sugar Beet in Field". Remote Sensing 12, n.º 2 (14 de enero de 2020): 269. http://dx.doi.org/10.3390/rs12020269.
Texto completoGrootswagers, Tijl, Susan G. Wardle y Thomas A. Carlson. "Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data". Journal of Cognitive Neuroscience 29, n.º 4 (abril de 2017): 677–97. http://dx.doi.org/10.1162/jocn_a_01068.
Texto completoElNakieb, Yaser, Mohamed T. Ali, Ahmed Elnakib, Ahmed Shalaby, Ali Mahmoud, Ahmed Soliman, Gregory Neal Barnes y Ayman El-Baz. "Understanding the Role of Connectivity Dynamics of Resting-State Functional MRI in the Diagnosis of Autism Spectrum Disorder: A Comprehensive Study". Bioengineering 10, n.º 1 (2 de enero de 2023): 56. http://dx.doi.org/10.3390/bioengineering10010056.
Texto completoTourville, Jason A., Alfonso Nieto-Castañón, Matthias Heyne y Frank H. Guenther. "Functional Parcellation of the Speech Production Cortex". Journal of Speech, Language, and Hearing Research 62, n.º 8S (29 de agosto de 2019): 3055–70. http://dx.doi.org/10.1044/2019_jslhr-s-csmc7-18-0442.
Texto completoJafari, Habib, Shamarina Shohaimi, Nader Salari, Ali Akbar Kiaei, Farid Najafi, Soleiman Khazaei, Mehrdad Niaparast, Anita Abdollahi y Masoud Mohammadi. "A full pipeline of diagnosis and prognosis the risk of chronic diseases using deep learning and Shapley values: The Ravansar county anthropometric cohort study". PLOS ONE 17, n.º 1 (20 de enero de 2022): e0262701. http://dx.doi.org/10.1371/journal.pone.0262701.
Texto completoRaspor, Eva, Peter K. Hahn, Tom Lancaster, David E. J. Linden, Florian Freudenberg, Andreas Reif y Robert A. Bittner. "S177. IMPACT OF NOS1AP AND ITS INTERACTION PARTNERS AT THE GLUTAMATERGIC SYNAPSE ON WORKING MEMORY NETWORKS - AN FMRI IMAGING GENETICS STUDY". Schizophrenia Bulletin 46, Supplement_1 (abril de 2020): S105. http://dx.doi.org/10.1093/schbul/sbaa031.243.
Texto completoColoigner †, Julie, Chau Vu †, Matt Borzage, Adam M. Bush, Natasha Lepore, Thomas D. Coates y John C. Wood. "Analysis of Hemodynamic Changes and Bold Signals of Sickle Cell Disease Patients during Desaturation". Blood 126, n.º 23 (3 de diciembre de 2015): 3384. http://dx.doi.org/10.1182/blood.v126.23.3384.3384.
Texto completoHoman, Philipp, Anil Malhotra, Todd Lencz y Pamela De Rosse. "M19. NIGROSTRIATAL CONNECTIVITY AND THE PREDICTION OF THOUGHT DISTURBANCE IN EARLY PSYCHOSIS". Schizophrenia Bulletin 46, Supplement_1 (abril de 2020): S140—S141. http://dx.doi.org/10.1093/schbul/sbaa030.331.
Texto completoRubio, Jose, Chrisina Fales, Anita Barber, Todd Lencz, Anil Malhotra y John Kane. "T23. ANTIPSYCHOTIC EXPOSURE AND STRIATAL FUNCTIONAL CONNECTIVITY IN PSYCHOSIS RELAPSE: A HYPOTHESIS GENERATING STUDY". Schizophrenia Bulletin 46, Supplement_1 (abril de 2020): S240. http://dx.doi.org/10.1093/schbul/sbaa029.583.
Texto completoEnguix, Vicente, Jeanette Kenley, David Luck, Julien Cohen-Adad y Gregory Anton Lodygensky. "NeoRS: A Neonatal Resting State fMRI Data Preprocessing Pipeline". Frontiers in Neuroinformatics 16 (17 de junio de 2022). http://dx.doi.org/10.3389/fninf.2022.843114.
Texto completoChen, Huihui, Yining Zhang, Limei Zhang, Lishan Qiao y Dinggang Shen. "Estimating Brain Functional Networks Based on Adaptively-Weighted fMRI Signals for MCI Identification". Frontiers in Aging Neuroscience 12 (14 de enero de 2021). http://dx.doi.org/10.3389/fnagi.2020.595322.
Texto completoDe Rosa, Alessandro Pasquale, Fabrizio Esposito, Paola Valsasina, Alessandro d’Ambrosio, Alvino Bisecco, Maria A. Rocca, Silvia Tommasin et al. "Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative". Journal of Neurology, 9 de noviembre de 2022. http://dx.doi.org/10.1007/s00415-022-11479-z.
Texto completoNotter, Michael P., Peer Herholz, Sandra Da Costa, Omer F. Gulban, Ayse Ilkay Isik, Anna Gaglianese y Micah M. Murray. "fMRIflows: A Consortium of Fully Automatic Univariate and Multivariate fMRI Processing Pipelines". Brain Topography, 27 de diciembre de 2022. http://dx.doi.org/10.1007/s10548-022-00935-8.
Texto completoSammartino, Francesco, Paul Taylor, Gang Chen, Richard C. Reynolds, Daniel Glen y Vibhor Krishna. "Functional Neuroimaging During Asleep DBS Surgery: A Proof of Concept Study". Frontiers in Neurology 12 (28 de junio de 2021). http://dx.doi.org/10.3389/fneur.2021.659002.
Texto completoPinsard, Basile, Arnaud Boutin, Julien Doyon y Habib Benali. "Integrated fMRI Preprocessing Framework Using Extended Kalman Filter for Estimation of Slice-Wise Motion". Frontiers in Neuroscience 12 (26 de abril de 2018). http://dx.doi.org/10.3389/fnins.2018.00268.
Texto completoLi, Qiang, Dinghong Gong, Jie Shen, Chang Rao, Lei Ni y Hongyi Zhang. "SF-MVPA: A from raw data to statistical results and surface space-based MVPA toolbox". Frontiers in Neuroscience 16 (21 de noviembre de 2022). http://dx.doi.org/10.3389/fnins.2022.1046752.
Texto completoXifra-Porxas, Alba, Michalis Kassinopoulos y Georgios D. Mitsis. "Physiological and motion signatures in static and time-varying functional connectivity and their subject identifiability". eLife 10 (3 de agosto de 2021). http://dx.doi.org/10.7554/elife.62324.
Texto completoBorkar, Kushal, Anusha Chaturvedi, P. K. Vinod y Raju Surampudi Bapi. "Ayu-Characterization of healthy aging from neuroimaging data with deep learning and rsfMRI". Frontiers in Computational Neuroscience 16 (12 de septiembre de 2022). http://dx.doi.org/10.3389/fncom.2022.940922.
Texto completoTarchi, Livio, Stefano Damiani, Teresa Fantoni, Tiziana Pisano, Giovanni Castellini, Pierluigi Politi y Valdo Ricca. "Centrality and interhemispheric coordination are related to different clinical/behavioral factors in attention deficit/hyperactivity disorder: a resting-state fMRI study". Brain Imaging and Behavior, 21 de julio de 2022. http://dx.doi.org/10.1007/s11682-022-00708-8.
Texto completoPereira-Sanchez, Victor, Alexandre R. Franco, Pilar de Castro-Manglano, Maria A. Fernandez-Seara, Maria Vallejo-Valdivielso, Azucena Díez-Suárez, Miguel Fernandez-Martinez et al. "Resting-State fMRI to Identify the Brain Correlates of Treatment Response to Medications in Children and Adolescents With Attention-Deficit/Hyperactivity Disorder: Lessons From the CUNMET Study". Frontiers in Psychiatry 12 (16 de noviembre de 2021). http://dx.doi.org/10.3389/fpsyt.2021.759696.
Texto completoPark, Junyung, Hyeon Seok Seok, Sang-Su Kim y Hangsik Shin. "Photoplethysmogram Analysis and Applications: An Integrative Review". Frontiers in Physiology 12 (1 de marzo de 2022). http://dx.doi.org/10.3389/fphys.2021.808451.
Texto completoSathe, Anish V., Michael Kogan, KiChang Kang, Jingya Miao, Mashaal Syed, Isaiah Ailes, Caio M. Matias et al. "Amplitude synchronization of spontaneous activity of medial and lateral temporal gyri reveals altered thalamic connectivity in patients with temporal lobe epilepsy". Scientific Reports 12, n.º 1 (1 de noviembre de 2022). http://dx.doi.org/10.1038/s41598-022-23297-4.
Texto completoLi, Shaoyi, Xiaotian Wang, Xi Yang, Kai Zhang y Saisai Niu. "Investigation of infrared dim and small target detection algorithm based on the visual saliency feature". Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 22 de diciembre de 2020, 095441002098095. http://dx.doi.org/10.1177/0954410020980955.
Texto completoDunn, Julia Passyn, Bidhan Lamicchane, Todd Braver, Tamara Hershey y Samuel Klein. "SAT-LB59 Functional MRI Study: Weight Loss Induced Changes in Taste Receipt-Induced Activation in the Striatum and Hypothalamus". Journal of the Endocrine Society 4, Supplement_1 (abril de 2020). http://dx.doi.org/10.1210/jendso/bvaa046.2262.
Texto completo