Co-Author
This page shows the publications co-authored by Bruce Fischl and Bruce Rosen.
Connection Strength
1.048
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Ciesielski KTR, Stern ME, Diamond A, Khan S, Busa EA, Goldsmith TE, van der Kouwe A, Fischl B, Rosen BR. Maturational Changes in Human Dorsal and Ventral Visual Networks. Cereb Cortex. 2019 12 17; 29(12):5131-5149.
Score: 0.236
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Reuter M, Gerstner ER, Rapalino O, Batchelor TT, Rosen B, Fischl B. Impact of MRI head placement on glioma response assessment. J Neurooncol. 2014 May; 118(1):123-9.
Score: 0.158
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Blackwell ML, Farrar CT, Fischl B, Rosen BR. Target-specific contrast agents for magnetic resonance microscopy. Neuroimage. 2009 Jun; 46(2):382-93.
Score: 0.114
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Fischl B, Stevens AA, Rajendran N, Yeo BT, Greve DN, Van Leemput K, Polimeni JR, Kakunoori S, Buckner RL, Pacheco J, Salat DH, Melcher J, Frosch MP, Hyman BT, Grant PE, Rosen BR, van der Kouwe AJ, Wiggins GC, Wald LL, Augustinack JC. Predicting the location of entorhinal cortex from MRI. Neuroimage. 2009 Aug 01; 47(1):8-17.
Score: 0.113
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Fischl B, van der Kouwe A, Destrieux C, Halgren E, Ségonne F, Salat DH, Busa E, Seidman LJ, Goldstein J, Kennedy D, Caviness V, Makris N, Rosen B, Dale AM. Automatically parcellating the human cerebral cortex. Cereb Cortex. 2004 Jan; 14(1):11-22.
Score: 0.078
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Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron. 2002 Jan 31; 33(3):341-55.
Score: 0.068
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Bianciardi M, Strong C, Toschi N, Edlow BL, Fischl B, Brown EN, Rosen BR, Wald LL. A probabilistic template of human mesopontine tegmental nuclei from in vivo 7T MRI. Neuroimage. 2018 04 15; 170:222-230.
Score: 0.049
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Holmes AJ, Hollinshead MO, O'Keefe TM, Petrov VI, Fariello GR, Wald LL, Fischl B, Rosen BR, Mair RW, Roffman JL, Smoller JW, Buckner RL. Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures. Sci Data. 2015; 2:150031.
Score: 0.043
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Greve DN, Svarer C, Fisher PM, Feng L, Hansen AE, Baare W, Rosen B, Fischl B, Knudsen GM. Cortical surface-based analysis reduces bias and variance in kinetic modeling of brain PET data. Neuroimage. 2014 May 15; 92:225-36.
Score: 0.039
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Cohen-Adad J, Benner T, Greve D, Kinkel RP, Radding A, Fischl B, Rosen BR, Mainero C. In vivo evidence of disseminated subpial T2* signal changes in multiple sclerosis at 7 T: a surface-based analysis. Neuroimage. 2011 Jul 01; 57(1):55-62.
Score: 0.032
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Catana C, van der Kouwe A, Benner T, Michel CJ, Hamm M, Fenchel M, Fischl B, Rosen B, Schmand M, Sorensen AG. Toward implementing an MRI-based PET attenuation-correction method for neurologic studies on the MR-PET brain prototype. J Nucl Med. 2010 Sep; 51(9):1431-8.
Score: 0.031
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Salat DH, Tuch DS, Greve DN, van der Kouwe AJ, Hevelone ND, Zaleta AK, Rosen BR, Fischl B, Corkin S, Rosas HD, Dale AM. Age-related alterations in white matter microstructure measured by diffusion tensor imaging. Neurobiol Aging. 2005 Aug-Sep; 26(8):1215-27.
Score: 0.021
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Makris N, Hodge SM, Haselgrove C, Kennedy DN, Dale A, Fischl B, Rosen BR, Harris G, Caviness VS, Schmahmann JD. Human cerebellum: surface-assisted cortical parcellation and volumetry with magnetic resonance imaging. J Cogn Neurosci. 2003 May 15; 15(4):584-99.
Score: 0.019
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Hadjikhani N, Sanchez Del Rio M, Wu O, Schwartz D, Bakker D, Fischl B, Kwong KK, Cutrer FM, Rosen BR, Tootell RB, Sorensen AG, Moskowitz MA. Mechanisms of migraine aura revealed by functional MRI in human visual cortex. Proc Natl Acad Sci U S A. 2001 Apr 10; 98(8):4687-92.
Score: 0.016
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Bar M, Tootell RB, Schacter DL, Greve DN, Fischl B, Mendola JD, Rosen BR, Dale AM. Cortical mechanisms specific to explicit visual object recognition. Neuron. 2001 Feb; 29(2):529-35.
Score: 0.016
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Moore CI, Stern CE, Corkin S, Fischl B, Gray AC, Rosen BR, Dale AM. Segregation of somatosensory activation in the human rolandic cortex using fMRI. J Neurophysiol. 2000 Jul; 84(1):558-69.
Score: 0.015
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.