Unified segmentation

Neural networks for pattern recognition

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Voxel-Based Morphometry—The Methods

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Whole Brain Segmentation

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Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

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Nonrigid registration using free-form deformations: application to breast mr images

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A nonparametric method for automatic correction of intensity nonuniformity in MRI data

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A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains

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Maximum Likelihood Reconstruction for Emission Tomography

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On the Statistical Analysis of Dirty Pictures

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Spatial registration and normalization of images

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Sequence-independent segmentation of magnetic resonance images

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Multi-modal volume registration by maximization of mutual information

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Design and construction of a realistic digital brain phantom

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Automated Image Registration: I. General Methods and Intrasubject, Intramodality Validation

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Landmark methods for forms without landmarks: morphometrics of group differences in outline shape

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Adaptive segmentation of MRI data

Wells, W. M., Grimson, W. E. L., Kikinis, R., & Jolesz, F. A. (1996) · IEEE Transactions on Medical Imaging · doi:10.1109/42.511747 · Cited by 1,291 · see citing works

Deformable templates using large deformation kinematics

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Automated model-based tissue classification of MR images of the brain

Van Leemput, K., Maes, F., Vandermeulen, D., & Suetens, P. (1999) · IEEE Transactions on Medical Imaging · doi:10.1109/42.811270 · Cited by 1,024 · see citing works

Automated Image Registration: II. Intersubject Validation of Linear and Nonlinear Models

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Magnetic Resonance Image Tissue Classification Using a Partial Volume Model

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B-spline signal processing. I. Theory

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Multimodal Image Coregistration and Partitioning—A Unified Framework

Ashburner, J., & Friston, K. J. (1997) · NeuroImage · doi:10.1006/nimg.1997.0290 · Cited by 932 · see citing works

Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI

MacDonald, D. J., Kabani, N. J., Avis, D., & Evans, A. C. (2000) · NeuroImage · doi:10.1006/nimg.1999.0534 · Cited by 850 · see citing works

Unbiased diffeomorphic atlas construction for computational anatomy

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Interpolation revisited [medical images application]

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Adaptive fuzzy segmentation of magnetic resonance images

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Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis

Zijdenbos, A. P., Forghani, R., & Evans, A. C. (2002) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2002.806283 · Cited by 755 · see citing works

Optimization of mutual information for multiresolution image registration

Unser, M. A., & Thévenaz, P. (2000) · IEEE Transactions on Image Processing · doi:10.1109/83.887976 · Cited by 694 · see citing works

Fast and robust parameter estimation for statistical partial volume models in brain MRI

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B-spline signal processing. II. Efficiency design and applications

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Automated model-based bias field correction of MR images of the brain

Leemput, K. V., Maes, F., Vandermeulen, D., & Suetens, P. (1999) · IEEE Transactions on Medical Imaging · doi:10.1109/42.811268 · Cited by 581 · see citing works

Parametric estimate of intensity inhomogeneities applied to MRI

Styner, M. A., Brechbühler, C., Szckely, G., & Gerig, G. (2000) · IEEE Transactions on Medical Imaging · doi:10.1109/42.845174 · Cited by 523 · see citing works

Landmark matching via large deformation diffeomorphisms

Joshi, S. C., & Miller, M. I. (2000) · IEEE Transactions on Image Processing · doi:10.1109/83.855431 · Cited by 500 · see citing works

Fast parametric elastic image registration

Kybic, J., & Unser, M. A. (2003) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.813139 · Cited by 473 · see citing works

Mathematical textbook of deformable neuroanatomies.

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Geodesic estimation for large deformation anatomical shape averaging and interpolation

Avants, B., & Gee, J. C. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.010 · Cited by 427 · see citing works

Fast Fluid Registration of medical images

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Group Actions, Homeomorphisms, and Matching: A General Framework

Miller, M. I., & Laurent Younes, B. (2001) · International Journal of Computer Vision · doi:10.1023/a:1011161132514 · Cited by 332 · see citing works

Structural Image Restoration through Deformable Templates

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The LONI Pipeline Processing Environment

Rex, D., Jeffrey, Q., & Toga, A. W. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00185-x · Cited by 310 · see citing works

Retrospective correction of MR intensity inhomogeneity by information minimization

Likar, B., Viergever, M. A., & Pernuš, F. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.974934 · Cited by 270 · see citing works

Magnetic Resonance Scanning and Epilepsy

Shorvon, S. D., Fish, D. R., Andermann, F., Bydder, G. M., & Stefan, H. (1994) · Springer eBooks · doi:10.1007/978-1-4615-2546-2 · Cited by 232 · see citing works

Spatial Normalization of 3D Brain Images Using Deformable Models

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Statistical methods in computational anatomy

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Statistics on diffeomorphisms via tangent space representations

Vaillant, M., Miller, M. I., Younes, L., & Trouvé, A. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.023 · Cited by 215 · see citing works

Computational anatomy: shape, growth, and atrophy comparison via diffeomorphisms

Miller, M. I. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.021 · Cited by 196 · see citing works

Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms

Laidlaw, D. H., Fleischer, K., & Barr, A. H. (1998) · IEEE Transactions on Medical Imaging · doi:10.1109/42.668696 · Cited by 191 · see citing works

High-Dimensional Image Registration Using Symmetric Priors

Ashburner, J., Andersson, J., & Friston, K. J. (1999) · NeuroImage · doi:10.1006/nimg.1999.0437 · Cited by 178 · see citing works

Qualitative and Quantitative Evaluation of Six Algorithms for Correcting Intensity Nonuniformity Effects

Arnold, J. B., Liow, J., Schaper, K. A., Stern, J. J., Sled, J. G., Shattuck, D. W., Worth, A. J., Cohen, M. S., Leahy, R. M., Mazziotta, J. C., et al. (2001) · NeuroImage · doi:10.1006/nimg.2001.0756 · Cited by 172 · see citing works

Reproducibility of BOLD-based functional MRI obtained at 4 T

Tegeler, C., Strother, S. C., Anderson, J. R., & Kim, S. (1999) · Human Brain Mapping · doi:10.1002/(sici)1097-0193(1999)7:4 · Cited by 121 · see citing works

Expert knowledge-guided segmentation system for brain MRI

Pitiot, A., Delingette, H., Thompson, P. M., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.040 · Cited by 118 · see citing works

Characterizing volume and surface deformations in an atlas framework: theory, applications, and implementation

Woods, R. P. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00019-3 · Cited by 104 · see citing works

Fiswidgets: A Graphical Computing Environment for Neuroimaging Analysis

Fissell, K., Tseytlin, E., Cunningham, D., Iyer, K., Carter, C. S., Schneider, W., & Cohen, J. D. (2003) · Neuroinformatics · doi:10.1385/ni:1:1:111 · Cited by 72 · see citing works

Accurate Template-Based Correction of Brain MRI Intensity Distortion With Application to Dementia and Aging

Studholme, C., Cardenas, V. A., Song, E., Ezekiel, F., Maudsley, A. A., & Weiner, M. W. (2004) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.820029 · Cited by 53 · see citing works

Inter-subject Registration of Functional and Anatomical Data Using SPM

Hellier, P., Ashburner, J., Corouge, I., et al. (2002) · Lecture notes in computer science · doi:10.1007/3-540-45787-9_74 · Cited by 44 · see citing works

Non-rigid Atlas-to-Image Registration by Minimization of Class-Conditional Image Entropy

D’Agostino, E., Maes, F., Vandermeulen, D., et al. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30135-6_91 · Cited by 34 · see citing works

A Statistical Framework for Partial Volume Segmentation

Leemput, K. V., Maes, F., Vandermeulen, D., et al. (2001) · Lecture notes in computer science · doi:10.1007/3-540-45468-3_25 · Cited by 11 · see citing works

Automatic correction of bias field in magnetic resonance images

Garza-Jinich, M., Yanez, O., Medina, V., et al. (2003) · International Conference on Image Analysis and Processing · doi:10.1109/iciap.1999.797685 · Cited by 1 · see citing works

Untitled work

Curio (2000) · doi:10.1002/(sici)1097-0193(200004)9:4

A fast diffeomorphic image registration algorithm

Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122 · see citing works

The multimodal brain tumor image segmentation benchmark (BRATS)

Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., et al. (2015) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2014.2377694 · Cited by 6,781 · see citing works

DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI

Yan (2010) · Frontiers in System Neuroscience · doi:10.3389/fnsys.2010.00013 · Cited by 3,475 · see citing works

A whole brain fMRI atlas generated via spatially constrained spectral clustering

Craddock, R. C., James, G. A., Holtzheimer, P. E., Hu, X. P., & Mayberg, H. S. (2012) · Human Brain Mapping · doi:10.1002/hbm.21333 · Cited by 1,636 · see citing works

A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics

Yan, C.-G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., Li, Q., Zuo, X.-N., Castellanos, F. X., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.004 · Cited by 1,461 · see citing works

Meditation experience is associated with differences in default mode network activity and connectivity

Brewer, J. A., Worhunsky, P. D., Gray, J. R., Tang, Y.-Y., Weber, J., & Kober, H. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1112029108 · Cited by 1,409 · see citing works

The Centiloid Project: standardizing quantitative amyloid plaque estimation by PET

Klunk, W. E., Koeppe, R. A., Price, J. C., Benzinger, T. L., Devous, M. D., Jagust, W. J., Johnson, K. A., Mathis, C. A., Minhas, D., Pontecorvo, M. J., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.07.003 · Cited by 1,348 · see citing works

Deep learning for brain MRI segmentation: state of the art and future directions

Akkus, Z., Galimzianova, A., Hoogi, A., Rubin, D. L., & Erickson, B. J. (2017) · Journal of Digital Imaging · doi:10.1007/s10278-017-9983-4 · Cited by 1,129 · see citing works

Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging

Jeurissen, B., Leemans, A., Tournier, J., Jones, D. K., & Sijbers, J. (2013) · Human Brain Mapping · doi:10.1002/hbm.22099 · Cited by 1,088 · see citing works

Limbic scars: long-term consequences of childhood maltreatment revealed by functional and structural magnetic resonance imaging

Dannlowski, U., Stuhrmann, A., Beutelmann, V., Zwanzger, P., Lenzen, T., Grotegerd, D., Domschke, K., Hohoff, C., Ohrmann, P., Bauer, J., et al. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.10.021 · Cited by 954 · see citing works

Evidence for grid cells in a human memory network

Doeller, C. F., Barry, C., & Burgess, N. (2010) · Nature · doi:10.1038/nature08704 · Cited by 828 · see citing works

Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

Wen, J., Thibeau-Sutre, E., Diaz-Melo, M., Samper-González, J., Routier, A., Bottani, S., Dormont, D., Durrleman, S., Burgos, N., & Colliot, O. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101694 · Cited by 809 · see citing works

Diagnostic value of plasma phosphorylated tau181 in Alzheimer's disease and frontotemporal lobar degeneration

Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) investigators, Thijssen, E. H., La Joie, R., Wolf, A., Strom, A., Wang, P., Iaccarino, L., Bourakova, V., Cobigo, Y., Heuer, H., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0762-2 · Cited by 761 · see citing works

Pupil diameter covaries with BOLD activity in human locus coeruleus

Murphy, P. R., O'Connell, R. G., O'Sullivan, M., Robertson, I. H., & Balsters, J. H. (2014) · Human Brain Mapping · doi:10.1002/hbm.22466 · Cited by 819 · see citing works

Pregnancy leads to long-lasting changes in human brain structure

Hoekzema, E., Barba-Müller, E., Pozzobon, C., Picado, M., Lucco, F., García-García, D., Soliva, J. C., Tobeña, A., Desco, M., Crone, E. A., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4458 · Cited by 788 · see citing works

Generalized Overlap Measures for Evaluation and Validation in Medical Image Analysis

Crum, W. R., Camara, O., & Hill, D. L. G. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.880587 · Cited by 776 · see citing works

Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI

Landau, S. M., Harvey, D., Madison, C. M., Koeppe, R. A., Reiman, E. M., Foster, N. L., Weiner, M. W., & Jagust, W. J. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2009.07.002 · Cited by 750 · see citing works

CNVs conferring risk of autism or schizophrenia affect cognition in controls

Stefansson, H., Meyer-Lindenberg, A., Steinberg, S., Magnusdottir, B., Morgen, K., Arnarsdottir, S., Bjornsdottir, G., Walters, G. B., Jonsdottir, G. A., Doyle, O. M., et al. (2014) · Nature · doi:10.1038/nature12818 · Cited by 699 · see citing works

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging

Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W.-J., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.068 · Cited by 739 · see citing works

Multi-atlas segmentation of biomedical images: A survey

Iglesias, J. E., & Sabuncu, M. R. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.06.012 · Cited by 667 · see citing works

Disrupted amygdalar subregion functional connectivity and evidence of a compensatory network in generalized anxiety disorder

Etkin, A., Prater, K. E., Schatzberg, A. F., Menon, V., & Greicius, M. D. (2009) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.104 · Cited by 664 · see citing works

Comparing predictors of conversion and decline in mild cognitive impairment

Landau, S. M., Harvey, D., Madison, C. M., Reiman, E. M., Foster, N. L., Aisen, P. S., Petersen, R. C., Shaw, L. M., Trojanowski, J. Q., Jack, C. R., et al. (2010) · Neurology · doi:10.1212/wnl.0b013e3181e8e8b8 · Cited by 616 · see citing works

Head motion during MRI acquisition reduces gray matter volume and thickness estimates

Reuter, M., Tisdall, M. D., Qureshi, A., Buckner, R. L., van der Kouwe, A. J. W., & Fischl, B. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.006 · Cited by 457 · see citing works

Dynamic Properties of Human Brain Structure: Learning-Related Changes in Cortical Areas and Associated Fiber Connections

Taubert, M., Draganski, B., Anwander, A., Müller, K., Horstmann, A., Villringer, A., & Ragert, P. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.2567-10.2010 · Cited by 514 · see citing works

The underlying anatomical correlates of long-term meditation: Larger hippocampal and frontal volumes of gray matter

Luders, E., Toga, A. W., Lepore, N., & Gaser, C. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.061 · Cited by 469 · see citing works

Binocular rivalry: frontal activity relates to introspection and action but not to perception

Frässle, S., Sommer, J., Jansen, A., Naber, M., & Einhäuser, W. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.4403-13.2014 · Cited by 409 · see citing works

Family Poverty Affects the Rate of Human Infant Brain Growth

Hanson, J. L., Hair, N., Shen, D. G., Shi, F., Gilmore, J. H., Wolfe, B. L., & Pollak, S. D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0080954 · Cited by 430 · see citing works

Evidence for Astrocytosis in Prodromal Alzheimer Disease Provided by ¹¹ C-Deuterium-L-Deprenyl: A Multitracer PET Paradigm Combining ¹¹ C-Pittsburgh Compound B and ¹⁸ F-FDG

Carter, S. F., Schöll, M., Almkvist, O., Wall, A., Engler, H., Långström, B., & Nordberg, A. (2012) · Journal of Nuclear Medicine · doi:10.2967/jnumed.110.087031 · Cited by 442 · see citing works

Training-induced structural changes in the adult human brain

Draganski, B., & May, A. (2008) · Behavioural Brain Research · doi:10.1016/j.bbr.2008.02.015 · Cited by 437 · see citing works

High pregnancy anxiety during mid-gestation is associated with decreased gray matter density in 6-9-year-old children.

Buss, C., Davis, E. P., Muftuler, L. T., Head, K., & Sandman, C. A. (2010) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2009.07.010 · Cited by 435 · see citing works

Anticipation of monetary and social reward differently activates mesolimbic brain structures in men and women

Spreckelmeyer, K. N., Krach, S., Kohls, G., Rademacher, L., Irmak, A., Konrad, K., Kircher, T., & Gründer, G. (2009) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsn051 · Cited by 425 · see citing works

Prefrontal Contributions to Metacognition in Perceptual Decision Making

Fleming, S. M., Huijgen, J., & Dolan, R. J. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.6489-11.2012 · Cited by 391 · see citing works

Brain mediators of predictive cue effects on perceived pain

Atlas, L. Y., Bolger, N., Lindquist, M. A., & Wager, T. D. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.0057-10.2010 · Cited by 389 · see citing works

Is there “one” DLPFC in cognitive action control? Evidence for heterogeneity from co-activation-based parcellation

Cieslik, E. C., Zilles, K., Caspers, S., Roski, C., Kellermann, T. S., Jakobs, O., Langner, R., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs256 · Cited by 391 · see citing works

Neuroimaging signatures of frontotemporal dementia genetics: C9ORF72, tau, progranulin and sporadics

Whitwell, J. L., Weigand, S. D., Boeve, B. F., Senjem, M. L., Gunter, J. L., DeJesus-Hernandez, M., Rutherford, N. J., Baker, M., Knopman, D. S., Wszolek, Z. K., et al. (2012) · Brain · doi:10.1093/brain/aws001 · Cited by 397 · see citing works

Automated segmentation of hippocampal subfields from ultra‐high resolution in vivo MRI

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Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease

Acosta-Cabronero, J., Williams, G. B., Pengas, G., & Nestor, P. J. (2010) · Brain · doi:10.1093/brain/awp257 · Cited by 393 · see citing works

Insular dysfunction within the salience network is associated with severity of symptoms and aberrant inter-network connectivity in major depressive disorder

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Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning

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