Magnetic Resonance Image Tissue Classification Using a Partial Volume Model

Theory of edge detection

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

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White matter changes with normal aging.

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Unified segmentation

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Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children

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

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Generalized Overlap Measures for Evaluation and Validation in Medical Image Analysis

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Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements

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Conversion of Mild Cognitive Impairment to Alzheimer Disease Predicted by Hippocampal Atrophy Maps

Apostolova, L. G., Dutton, R. A., Dinov, I. D., Hayashi, K. M., Toga, A. W., Cummings, J. L., & Thompson, P. M. (2006) · Archives of Neurology · doi:10.1001/archneur.63.5.693 · Cited by 553

Deep MRI brain extraction: A 3D convolutional neural network for skull stripping

Kleesiek, J., Urban, G., Hubert, A., Schwarz, D., Maier-Hein, K., Bendszus, M., & Biller, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.024 · Cited by 505

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

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Greater Cortical Gray Matter Density in Lithium-Treated Patients with Bipolar Disorder

Bearden, C. E., Thompson, P. M., Dalwani, M., Hayashi, K. M., Lee, A. D., Nicoletti, M., Trakhtenbroit, M., Glahn, D. C., Brambilla, P., Sassi, R. B., et al. (2007) · Biological Psychiatry · doi:10.1016/j.biopsych.2006.10.027 · Cited by 289

Automated graph-based analysis and correction of cortical volume topology

Shattuck, D. W., & Leahy, R. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.963819 · Cited by 215

Evaluating fMRI preprocessing pipelines

Strother, S. C. (2006) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2006.1607667 · Cited by 169

Widespread Cortical Thinning Is a Robust Anatomical Marker for Attention-Deficit/Hyperactivity Disorder

Narr, K. L., Woods, R. P., Lin, J., Kim, J., Phillips, O. R., Del'Homme, M., Caplan, R., Toga, A. W., McCracken, J. T., & Levitt, J. G. (2009) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/chi.0b013e3181b395c0 · Cited by 168

Reduced white matter integrity in attention-deficit hyperactivity disorder

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Comparative assessment of statistical brain MR image segmentation algorithms and their impact on partial volume correction in PET

Zaidi, H., Ruest, T., Schoenahl, F., & Montandon, M.-L. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.05.031 · Cited by 108

Label-aligned multi-task feature learning for multimodal classification of alzheimer’s disease and mild cognitive impairment

Initiative, T. A. D. N., Zu, C., Jie, B., Liu, M., Chen, S., Shen, D., & Zhang, D. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-015-9480-7 · Cited by 95

Mapping brain size and cortical gray matter changes in elderly depression

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Automated fetal brain segmentation from 2D MRI slices for motion correction

Keraudren, K., Kuklisova-Murgasova, M., Kyriakopoulou, V., Malamateniou, C., Rutherford, M. A., Kainz, B., Hajnal, J. V., & Rueckert, D. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.023 · Cited by 91

Gender differences in the left inferior frontal gyrus in normal children

Blanton, R. E., Levitt, J. G., Peterson, J. R., Fadale, D., Sporty, M. L., Lee, M., To, D., Mormino, E. C., Thompson, P. M., McCracken, J. T., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.01.010 · Cited by 90

Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training

Thakur, S., Doshi, J., Pati, S., Rathore, S., Sako, C., Bilello, M., Ha, S. M., Shukla, G., Flanders, A., Kotrotsou, A., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117081 · Cited by 84

Early life stress is associated with default system integrity and emotionality during infancy

Graham, A. M., Pfeifer, J. H., Fisher, P. A., Carpenter, S., & Fair, D. A. (2015) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12409 · Cited by 84

Fiber tractography reveals disruption of temporal lobe white matter tracts in schizophrenia

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Posterior structural brain volumes differ in maltreated youth with and without chronic posttraumatic stress disorder

De Bellis, M. D., Hooper, S. R., Chen, S. D., Provenzale, J. M., Boyd, B. D., Glessner, C. E., MacFall, J. R., Payne, M. E., Rybczynski, R., & Woolley, D. P. (2015) · Development and Psychopathology · doi:10.1017/s0954579415000942 · Cited by 75

Bayesian convolutional neural network based MRI brain extraction on nonhuman primates

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A review of Methods for Bias Correction in Medical Images

Song, S., Zheng, Y., & He, Y. (2017) · Biomedical Engineering Review · doi:10.18103/bme.v3i1.1550 · Cited by 62

The age-related posterior-anterior shift as revealed by voxelwise analysis of functional brain networks

McCarthy, P., Benuskova, L., & Franz, E. A. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00301 · Cited by 48

Puberty in the corpus callosum

Chavarria, M. C., Sánchez, F. J., Chou, Y.-Y., Thompson, P. M., & Luders, E. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.01.030 · Cited by 46

Convolutional neural network based prediction of conversion from mild cognitive impairment to alzheimer’s disease: a technique using hippocampus extracted from mri

MUKHTAR, G., & FARHAN, S. (2020) · Advances in Electrical and Computer Engineering · doi:10.4316/aece.2020.02013 · Cited by 19