{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T14:59:01Z","timestamp":1763564341988,"version":"build-2065373602"},"reference-count":67,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T00:00:00Z","timestamp":1711584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Hoblitzelle Foundation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Magnetoencephalography (MEG) is a noninvasive neuroimaging technique widely recognized for epilepsy and tumor mapping. MEG clinical reporting requires a multidisciplinary team, including expert input regarding each dipole\u2019s anatomic localization. Here, we introduce a novel tool, the \u201cMagnetoencephalography Atlas Viewer\u201d (MAV), which streamlines this anatomical analysis. The MAV normalizes the patient\u2019s Magnetic Resonance Imaging (MRI) to the Montreal Neurological Institute (MNI) space, reverse-normalizes MNI atlases to the native MRI, identifies MEG dipole files, and matches dipoles\u2019 coordinates to their spatial location in atlas files. It offers a user-friendly and interactive graphical user interface (GUI) for displaying individual dipoles, groups, coordinates, anatomical labels, and a tri-planar MRI view of the patient with dipole overlays. It evaluated over 273 dipoles obtained in clinical epilepsy subjects. Consensus-based ground truth was established by three neuroradiologists, with a minimum agreement threshold of two. The concordance between the ground truth and MAV labeling ranged from 79% to 84%, depending on the normalization method. Higher concordance rates were observed in subjects with minimal or no structural abnormalities on the MRI, ranging from 80% to 90%. The MAV provides a straightforward MEG dipole anatomic localization method, allowing a nonspecialist to prepopulate a report, thereby facilitating and reducing the time of clinical reporting.<\/jats:p>","DOI":"10.3390\/jimaging10040080","type":"journal-article","created":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T13:20:53Z","timestamp":1711632053000},"page":"80","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Magnetoencephalography Atlas Viewer for Dipole Localization and Viewing"],"prefix":"10.3390","volume":"10","author":[{"given":"N.C.d.","family":"Fonseca","sequence":"first","affiliation":[{"name":"MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"given":"Jason","family":"Bowerman","sequence":"additional","affiliation":[{"name":"Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1516-6831","authenticated-orcid":false,"given":"Pegah","family":"Askari","sequence":"additional","affiliation":[{"name":"MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Biomedical Engineering Department, University of Texas Arlington, Arlington, TX 76019, USA"},{"name":"Biomedical Engineering Department, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"given":"Amy L.","family":"Proskovec","sequence":"additional","affiliation":[{"name":"MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"given":"Fabricio Stewan","family":"Feltrin","sequence":"additional","affiliation":[{"name":"MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"given":"Daniel","family":"Veltkamp","sequence":"additional","affiliation":[{"name":"MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"given":"Heather","family":"Early","sequence":"additional","affiliation":[{"name":"MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2835-986X","authenticated-orcid":false,"given":"Ben C.","family":"Wagner","sequence":"additional","affiliation":[{"name":"Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8765-6584","authenticated-orcid":false,"given":"Elizabeth M.","family":"Davenport","sequence":"additional","affiliation":[{"name":"MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Biomedical Engineering Department, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]},{"given":"Joseph A.","family":"Maldjian","sequence":"additional","affiliation":[{"name":"MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Biomedical Engineering Department, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1103\/RevModPhys.65.413","article-title":"Magnetoencephalography\u2014Theory, instrumentation, and applications to noninvasive studies of the working human brain","volume":"65","author":"Hari","year":"1993","journal-title":"Rev. Mod. Phys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1113\/jphysiol.2006.105379","article-title":"Contributions of principal neocortical neurons to magnetoencephalography and electroencephalography signals","volume":"575","author":"Murakami","year":"2006","journal-title":"J. Physiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1720","DOI":"10.1016\/j.clinph.2018.03.042","article-title":"IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG)","volume":"129","author":"Hari","year":"2018","journal-title":"Clin. Neurophysiol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1813","DOI":"10.1002\/hbm.20792","article-title":"Clinical applications of magnetoencephalography","volume":"30","author":"Stufflebeam","year":"2009","journal-title":"Hum. Brain Mapp."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"938","DOI":"10.1152\/jn.00530.2020","article-title":"Magnetoencephalography: Physics, techniques, and applications in the basic and clinical neurosciences","volume":"125","author":"Kim","year":"2021","journal-title":"J. Neurophysiol."},{"key":"ref_6","first-page":"355","article-title":"American Clinical Magnetoencephalography Society Clinical Practice Guideline 2: Presurgical functional brain mapping using magnetic evoked fields","volume":"28","author":"Burgess","year":"2011","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.nic.2020.02.005","article-title":"Presurgical functional mapping with magnetoencephalography","volume":"30","author":"Bowyer","year":"2020","journal-title":"Neuroimaging Clin."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Fred, A.L., Kumar, S.N., Kumar Haridhas, A., Ghosh, S., Purushothaman Bhuvana, H., Sim, W.K.J., Vimalan, V., Givo, F.A.S., Jousm\u00e4ki, V., and Padmanabhan, P. (2022). A Brief Introduction to Magnetoencephalography (MEG) and Its Clinical Applications. Brain Sci., 12.","DOI":"10.3390\/brainsci12060788"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2935","DOI":"10.1093\/brain\/aww215","article-title":"Correlating magnetoencephalography to stereo-electroencephalography in patients undergoing epilepsy surgery","volume":"139","author":"Murakami","year":"2016","journal-title":"Brain"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"E9","DOI":"10.3171\/2013.4.FOCUS1357","article-title":"Correlation between magnetoencephalography-based \u201cclusterectomy\u201d and postoperative seizure freedom","volume":"34","author":"Vadera","year":"2013","journal-title":"Neurosurg. Focus"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"E16","DOI":"10.3171\/2020.1.FOCUS19877","article-title":"Utility of magnetic source imaging in nonlesional focal epilepsy: A prospective study","volume":"48","author":"Mohamed","year":"2020","journal-title":"Neurosurg. Focus"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.nic.2020.02.001","article-title":"Magnetoencephalography signal processing, forward modeling, inverse source imaging, and coherence analysis","volume":"30","author":"Huang","year":"2020","journal-title":"Neuroimaging Clin."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"14","DOI":"10.4103\/0972-2327.61271","article-title":"Clinical applications of magnetoencephalography in epilepsy","volume":"13","author":"Ray","year":"2010","journal-title":"Ann. Indian Acad. Neurol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.nic.2020.02.004","article-title":"MEG for greater sensitivity and more precise localization in epilepsy","volume":"30","author":"Burgess","year":"2020","journal-title":"Neuroimaging Clin."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1097\/WNP.0000000000000487","article-title":"The value of source localization for clinical magnetoencephalography: Beyond the equivalent current dipole","volume":"37","author":"Tenney","year":"2020","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1097\/WNP.0000000000000542","article-title":"Towards Best Practices in Clinical Magnetoencephalography: Patient Preparation and Data Acquisition","volume":"37","author":"Mosher","year":"2020","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"722986","DOI":"10.3389\/fneur.2021.722986","article-title":"Practical Fundamentals of Clinical MEG Interpretation in Epilepsy","volume":"12","author":"Laohathai","year":"2021","journal-title":"Front. Neurol."},{"key":"ref_18","first-page":"348","article-title":"American clinical magnetoencephalography society clinical practice guideline 1: Recording and analysis of spontaneous cerebral activity","volume":"28","author":"Bagic","year":"2011","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.eplepsyres.2008.07.013","article-title":"Characteristics of MEG and MRI between Taylor\u2019s focal cortical dysplasia (type II) and other cortical dysplasia: Surgical outcome after complete resection of MEG spike source and MR lesion in pediatric cortical dysplasia","volume":"82","author":"Widjaja","year":"2008","journal-title":"Epilepsy Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1097\/WNP.0000000000000700","article-title":"MEG Reporting","volume":"37","author":"Burgess","year":"2020","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Bock, E., and Baillet, S. (April, January 28). MEG-Clinic: A Comprehensive Software Solution for Routine MEG Analysis. Proceedings of the 17th International Conference on Biomagnetism Advances in Biomagnetism\u2013Biomag2010, Dubrovnik, Croatia.","DOI":"10.1007\/978-3-642-12197-5_26"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"119373","DOI":"10.1016\/j.neuroimage.2022.119373","article-title":"The natural frequencies of the resting human brain: An MEG-based atlas","volume":"258","author":"Capilla","year":"2022","journal-title":"NeuroImage"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"4685","DOI":"10.1002\/hbm.25578","article-title":"A systematic evaluation of source reconstruction of resting MEG of the human brain with a new high-resolution atlas: Performance, precision, and parcellation","volume":"42","author":"Tait","year":"2021","journal-title":"Hum. Brain Mapp."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2879","DOI":"10.1109\/TMI.2022.3173743","article-title":"Fully-Automated Spike Detection and Dipole Analysis of Epileptic MEG Using Deep Learning","volume":"41","author":"Hirano","year":"2022","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1016\/S1053-8119(03)00169-1","article-title":"An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets","volume":"19","author":"Maldjian","year":"2003","journal-title":"Neuroimage"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1002\/epi4.12499","article-title":"Validation of semi-automated anatomically labeled SEEG contacts in a brain atlas for mapping connectivity in focal epilepsy","volume":"6","author":"Taylor","year":"2021","journal-title":"Epilepsia Open"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"120292","DOI":"10.1016\/j.neuroimage.2023.120292","article-title":"A systematic comparison of VBM pipelines and their application to age prediction","volume":"279","author":"Antonopoulos","year":"2023","journal-title":"Neuroimage"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.jneumeth.2009.09.005","article-title":"Approximate average head models for EEG source imaging","volume":"185","author":"Kochen","year":"2009","journal-title":"J. Neurosci. Methods"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"119165","DOI":"10.1016\/j.neuroimage.2022.119165","article-title":"Sharing individualised template MRI data for MEG source reconstruction: A solution for open data while keeping subject confidentiality","volume":"254","author":"Vinding","year":"2022","journal-title":"NeuroImage"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1016\/j.neuroimage.2008.12.037","article-title":"Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration","volume":"46","author":"Klein","year":"2009","journal-title":"NeuroImage"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1002\/(SICI)1097-0193(1999)7:4<254::AID-HBM4>3.0.CO;2-G","article-title":"Nonlinear spatial normalization using basis functions","volume":"7","author":"Ashburner","year":"1999","journal-title":"Hum. Brain Mapp."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1016\/j.neuroimage.2007.04.065","article-title":"Spatial normalization of lesioned brains: Performance evaluation and impact on fMRI analyses","volume":"37","author":"Crinion","year":"2007","journal-title":"NeuroImage"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1006\/nimg.2002.1132","article-title":"Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images","volume":"17","author":"Jenkinson","year":"2002","journal-title":"NeuroImage"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/S1361-8415(01)00036-6","article-title":"A global optimisation method for robust affine registration of brain images","volume":"5","author":"Jenkinson","year":"2001","journal-title":"Med. Image Anal."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.neuroimage.2009.06.060","article-title":"Accurate and robust brain image alignment using boundary-based registration","volume":"48","author":"Greve","year":"2009","journal-title":"NeuroImage"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"S173","DOI":"10.1016\/j.neuroimage.2008.10.055","article-title":"Bayesian analysis of neuroimaging data in FSL","volume":"45","author":"Woolrich","year":"2009","journal-title":"Neuroimage"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","article-title":"Advances in functional and structural MR image analysis and implementation as FSL","volume":"23","author":"Smith","year":"2004","journal-title":"Neuroimage"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1016\/j.neuroimage.2011.09.015","article-title":"FSL","volume":"62","author":"Jenkinson","year":"2012","journal-title":"NeuroImage"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Gaser, C., Dahnke, R., Thompson, P.M., Kurth, F., Luders, E., and Alzheimer\u2019s Disease Neuroimaging Initiative (Neuroscience, 2022). CAT\u2014A Computational Anatomy Toolbox for the Analysis of Structural MRI Data, Neuroscience.","DOI":"10.1101\/2022.06.11.495736"},{"key":"ref_40","unstructured":"Friston, K.J. (1994). Functional Neuroimaging: Technical Foundations, Academic Press."},{"key":"ref_41","unstructured":"Talairach, J., Tournoux, P., and Rayport, M. (1988). Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging, Cambridge University Press."},{"key":"ref_42","unstructured":"Evans, A.C., Collins, D.L., Mills, S.R., Brown, E.D., Kelly, R.L., and Peters, T.M. (November, January 31). 3D statistical neuroanatomical models from 305 MRI volumes. Proceedings of the 1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference, San Francisco, CA, USA."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1038\/nrn756","article-title":"The problem of functional localization in the human brain","volume":"3","author":"Brett","year":"2002","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/1053-8119(92)90006-9","article-title":"Anatomical mapping of functional activation in stereotactic coordinate space","volume":"1","author":"Evans","year":"1992","journal-title":"NeuroImage"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.neuroimage.2004.12.007","article-title":"The Talairach coordinate of a point in the MNI space: How to interpret it","volume":"25","author":"Chau","year":"2005","journal-title":"NeuroImage"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1098\/rstb.2001.0915","article-title":"A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)","volume":"356","author":"Mazziotta","year":"2001","journal-title":"Philos. Trans. R. Soc. London. Ser. B Biol. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1006\/nimg.1995.1012","article-title":"A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development","volume":"2","author":"Mazziotta","year":"1995","journal-title":"NeuroImage"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1002\/1097-0193(200007)10:3<120::AID-HBM30>3.0.CO;2-8","article-title":"Automated Talairach Atlas labels for functional brain mapping","volume":"10","author":"Lancaster","year":"2000","journal-title":"Hum. Brain Mapp."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1002\/(SICI)1097-0193(1997)5:4<238::AID-HBM6>3.0.CO;2-4","article-title":"Automated labeling of the human brain: A preliminary report on the development and evaluation of a forward-transform method","volume":"5","author":"Lancaster","year":"1997","journal-title":"Hum. Brain Mapp."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"67","DOI":"10.2478\/s13380-012-0009-x","article-title":"Brodmann\u2019s map of the human cerebral cortex\u2014Or Brodmann\u2019s maps?","volume":"3","author":"Cepanec","year":"2012","journal-title":"Transl. Neurosci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1006\/nimg.2001.0978","article-title":"Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain","volume":"15","author":"Landeau","year":"2002","journal-title":"NeuroImage"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1002\/(SICI)1097-0193(1997)5:4<228::AID-HBM4>3.0.CO;2-5","article-title":"Use of anatomical parcellation to catalog and study structure-function relationships in the human brain","volume":"5","author":"Tzourio","year":"1997","journal-title":"Hum. Brain Mapp."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.neuroimage.2008.07.009","article-title":"Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter","volume":"43","author":"Oishi","year":"2008","journal-title":"Neuroimage"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"306","DOI":"10.3389\/fnhum.2017.00306","article-title":"Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks","volume":"11","author":"Figley","year":"2017","journal-title":"Front. Hum. Neurosci."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"585","DOI":"10.3389\/fnhum.2015.00585","article-title":"Probabilistic atlases of default mode, executive control and salience network white matter tracts: An fMRI-guided diffusion tensor imaging and tractography study","volume":"9","author":"Figley","year":"2015","journal-title":"Front. Hum. Neurosci."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1007\/s12021-016-9320-y","article-title":"A Stereotactic Probabilistic Atlas for the Major Cerebral Arteries","volume":"15","author":"Dunas","year":"2017","journal-title":"Neuroinformatics"},{"key":"ref_57","unstructured":"Alem\u00e1n-G\u00f3mez, Y. (2006, January 11\u201315). IBASPM: Toolbox for automatic parcellation of brain structures. Proceedings of the 12th Annual Meeting of the Organization for Human Brain Mapping, Florence, Italy."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"503","DOI":"10.3389\/fnins.2016.00503","article-title":"Reproducibility and Bias in Healthy Brain Segmentation: Comparison of Two Popular Neuroimaging Platforms","volume":"10","author":"Tudorascu","year":"2016","journal-title":"Front. Neurosci."},{"key":"ref_59","first-page":"13","article-title":"Quantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation","volume":"4","author":"Kazemi","year":"2014","journal-title":"J. Biomed. Phys. Eng."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1002\/mrm.1910150117","article-title":"Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE)","volume":"15","author":"Brookeman","year":"1990","journal-title":"Magn. Reson. Med."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1002\/jmri.1880010509","article-title":"Rapid three-dimensional T1-weighted MR imaging with the MP-RAGE sequence","volume":"1","author":"Brookeman","year":"1991","journal-title":"J. Magn. Reson. Imaging"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/j.neuroimage.2009.02.009","article-title":"T1 weighted brain images at 7 Tesla unbiased for Proton Density, T2\u204e contrast and RF coil receive B1 sensitivity with simultaneous vessel visualization","volume":"46","author":"Auerbach","year":"2009","journal-title":"Neuroimage"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1016\/j.neuroimage.2009.10.002","article-title":"MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field","volume":"49","author":"Marques","year":"2010","journal-title":"Neuroimage"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Marques, J.P., and Gruetter, R. (2013). New developments and applications of the MP2RAGE sequence-focusing the contrast and high spatial resolution R1 mapping. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0069294"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"O\u2019Brien, K.R., Kober, T., Hagmann, P., Maeder, P., Marques, J., Lazeyras, F., Krueger, G., and Roche, A. (2014). Robust T1-weighted structural brain imaging and morphometry at 7T using MP2RAGE. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0099676"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Choi, U.S., Kawaguchi, H., Matsuoka, Y., Kober, T., and Kida, I. (2019). Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0210803"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.neuroimage.2010.07.033","article-title":"Unbiased average age-appropriate atlases for pediatric studies","volume":"54","author":"Fonov","year":"2011","journal-title":"Neuroimage"}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/10\/4\/80\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:19:52Z","timestamp":1760105992000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/10\/4\/80"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,28]]},"references-count":67,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["jimaging10040080"],"URL":"https:\/\/doi.org\/10.3390\/jimaging10040080","relation":{},"ISSN":["2313-433X"],"issn-type":[{"type":"electronic","value":"2313-433X"}],"subject":[],"published":{"date-parts":[[2024,3,28]]}}}