Lab Director
Bruce Fischl |
Lab Manager
Allison Stevens |
Faculty
Iman Aganj | André van der Kouwe |
Jean Augustinack | Anastasia Yendiki |
Douglas Greve | Lilla Zöllei |
Caroline Magnain | Hui Wang |
Robert Frost | Adrian Dalca |
Affiliated Faculty
Brian Edlow | David Salat |
Martin Reuter | Dylan Tisdall |
Juan Eugenio Iglesias | Koen Van Leemput |
Thomas Yeo |
Research Fellows
Divya Varadarajan | Aina Frau-Pascual |
Malte Hoffmann | Jian (Andrew) Li |
Danielle Pace | Chiara Maffei |
Yael Balbastre | Sean Isaac Young |
Jan Oltmer | Chao Liu |
Developers
Andrew Hoopes | Ruopeng Wang |
Rob D. | Paul Wighton |
Research Technicians
Leah Morgan | Kimberly Nestor |
Emily Williams | Holly Freeman |
Robert Jones | Natalya Slepneva |
Matt Vera | Devani Cordero |
Josue Llamas Rodriguez | William Ammon |
Jocelyn Mora | Jackson Nolan |
Erendira Garcia Pallares | Mingu Kim |
Students
Collaborators
Alumni
Lab Director
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Bruce Fischl |
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Professor in Radiology at Harvard Medical School Neuroscientist at Massachusetts General Hospital Director, Computational Core at Martinos Center, MGH Department of Radiology, MGH |
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PhD, Cognitive and Neural Systems, Boston University | |
fischl [at] nmr.mgh.harvard.edu |
Bruce's current research involves the development of techniques for the automatic construction and utilization of geometrically accurate and topologically correct models of the human cerebral cortex. These models are based on high-resolution T1-weighted MR images, and have a number of uses. Their primary utility has been as a domain for the visualization of cortical neuroimaging data, as the metric structure of the cortex is significantly more visible when it is viewed as a surface, but they have also been useful as a substrate for combining neuroimaging data from different imaging modalities in order to obtain high spatial and temporal resolution. In addition, Bruce has developed a technique that exploits the correlation between cortical folding patterns and cortical function in order to generate a more accurate mapping across different brains. This high-dimensional nonlinear registration procedure results in a substantial increase in statistical power over more standard methods of inter-subject averaging, and allows the automatic and accurate labeling of many anatomical features of the cortex. While the primary use of the cortical models has been for visualization and more recently high-dimensional inter-subject registration, the models also represent a rich source of information regarding the morphometric properties of the cortex. Another focus of Bruce's research has been increasing the accuracy of the models of both the gray/white surface as well as the pial surface itself. The combination of these two surfaces allows one to measure the thickness of the gray matter of the cortex. The thickness of the cortical ribbon is of great clinical and research significance as many neurodegenerative diseases result in progressive, regionally specific atrophy of the cortical gray matter. This research has shown that measures of thickness using the cortical models are accurate to within ¼ millimeter, or substantially less than the size of a typical MR voxel.
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Lab Manager
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Allison Stevens |
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Research Lab Manager, Sr. Department of Radiology, MGH |
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MA, Psychology, Boston University | |
astevens [at] nmr.mgh.harvard.edu |
Allison serves as the lab manager for LCN. She is also responsible for organizing local and international FreeSurfer courses and helping with FreeSurfer testing and development. Aside from that, she is primarily involved with ex vivo brain imaging and processing on 3T and 7T scanners. |
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Faculty
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Iman Aganj |
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Assistant Professor of Radiology at Harvard Medical School Research Staff at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Electrical Engineering, University of Minnesota | |
iaganj [at] mgh.harvard.edu |
Iman’s work at LCN involves mostly medical image registration and segmentation, and brain connectivity analysis. |
Personal website |
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Jean Augustinack |
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Assistant Professor in Radiology at Harvard Medical School Assistant in Neuroscience at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Anatomy & Cell Biology, University of Iowa | |
jean [at] nmr.mgh.harvard.edu |
My research focuses on two main concentrations: brain mapping and neuropathological systems in Alzheimer's disease. We study healthy brains to understand neuroanatomical systems, improve cortical area localization, and examine Alzheimer’s samples to investigate neurofibrillary, neuronal and morphological changes in the medial temporal lobe.
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Robert Frost |
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Instructor in Radiology at Harvard Medical School Instructor at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, MRI Physics, University of Oxford | |
srfrost [at] mgh.harvard.edu |
Robert works on MRI sequence development. He focuses on real-time techniques to correct for motion during scans and acquisition strategies for high-resolution diffusion imaging. |
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Adrian Dalca |
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Assistant Professor in Radiology at Harvard Medical School Research Staff at Massachusetts General Hospital Department of Radiology, MGH |
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adalca [at] mit.edu |
Adrian's research focuses on probabilistic models and machine learning techniques that capture relationships between medical images, clinical diagnoses, and other complex medical data. His work spans medical image analysis, computer vision, machine learning and computational biology. Adrian obtained his PhD from CSAIL, MIT, and his BS and MS in Computer Science from the University of Toronto. |
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Douglas Greve |
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Assistant Professor in Radiology at Harvard Medical School Assistant in Neuroscience at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Cognitive & Neural Systems, Boston University | |
greve [at] nmr.mgh.harvard.edu |
Doug's primary research has been in the analysis and integration of multi-modal MRI. His primary expertise is in the analysis of fMRI at the time series and group levels. Doug has been one of the core FreeSurfer software developers since 1999 during which time he has written the fMRI analysis stream distributed with FreeSurfer (FS-FAST). He has been a member of the Functional Biomedical Informatics Research Network (fBIRN) with the primary responsibility of researching methods to quantify, calibrate, and remove site-specific artifacts from fMRI. He has authored the Boundary-based Registration algorithm which registers an arbitrary MRI volume (eg, fMRI, DTI, ASL) to the same-subject's structural MRI using strong anatomical priors. This allows accurate multi-modal integration. Doug has also written software to analyze DTI and ASL data. In addition to his direct fMRI research, he has led a project using near-infrared spectroscopy (NIRS) optical imaging and physiological monitoring to de-noise fMRI data. |
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Caroline Magnain |
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Instructor in Radiology at Harvard Medical School Instructor at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Optics, INSP UPMC, Paris, France | |
cmagnain [at] nmr.mgh.harvard.edu |
Caroline is working on 3D high resolution human brain imaging using Optical Coherence Tomography (OCT). Part of her study is to identify anatomical brain regions (Brodmann areas) by examining optical property changes in the cortical layers. The tissue samples are then registered to high resolution MRI imaging data to look for potential MR markers of the boundaries identified in OCT. The boundaries observed using OCT are validated with histology/immunochemistry. Additionally, Caroline is investigating using OCT to perform high resolution tractography, which she compares to ex vivo MRI diffusion data. |
Personal website |
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André van der Kouwe |
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Associate Professor in Radiology at Harvard Medical School Assistant in Physics at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Biomedical Engineering, Ohio State University | |
andre [at] nmr.mgh.harvard.edu |
André has been the key developer of sequences that are optimal with respect to brain morphometry, and more recently M. Dylan Tisdall has worked with André to develop structural sequences with embedded real-time motion correction that promise to open up structural imaging to an array of clinical populations that were difficult or impossible to image previously. |
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Anastasia Yendiki |
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Associate Professor at Harvard Medical School Associate Investigator at Massachusetts General Hospital Martinos Center for Biomedical Imaging |
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PhD, Electrical Engineering: Systems, The University of Michigan, Ann Arbor, MI | |
ayendiki [at] mgh.harvard.edu |
Anastasia is responsible for the development of the diffusion MRI analysis tools in FreeSurfer, including TRACULA (TRActs Constrained by UnderLying Anatomy), a method for automatically reconstructing a set of major white matter pathways from diffusion MRI data using global probabilistic tractography with anatomical priors. She is also interested in ex vivo imaging of human brain circuits with diffusion MRI and optical imaging to both validate and train algorithms for in vivo tractography. Website: https://scholar.harvard.edu/a-y |
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Lilla Zöllei |
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Assistant Professor in Radiology at Harvard Medical School |
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PhD, Electricial Eng & Computer Sci, MIT | |
lzollei [at] nmr.mgh.harvard.edu |
Lilla is currently focusing on perinatal and child brain imaging projects. She is developing a segmentation and surface reconstruction pipeline for infants and is interested in computing automated tractography solutions on this same population. Additionally, she is also invested in learning about perinatal brain development using various ex vivo imaging techniques (MRI, OCT) and is collaborating with clinical experts to characterize brains of infants who passed away from Suddent Infant Death Syndrom (SIDS). She is interested in research initiatives where statistical and information theoretic approaches can be applied as well as deep learning. |
Personal website |
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Affiliated Faculty
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Koen Van Leemput |
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Assistant Professor in Radiology at Harvard Medical School Assistant Neuroscientist at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Electrical Engineering, K.U.Leuven, Belgium | |
koen [at] nmr.mgh.harvard.edu |
Koen is an expert in model-based segmentation and registration of brain imaging data. He has developed the FreeSurfer techniques to perform a fully-automated segmentation of the subfields of the hippocampus. |
Personal website |
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Martin Reuter |
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Assistant Professor of Radiology and Neurology at Harvard Medical School Assistant in Neuroscience at Massachusetts General Hospital Department of Neurology, MGH Department of Radiology, MGH |
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PhD, Leibniz University Hannover | |
mreuter [at] nmr.mgh.harvard.edu |
Martin has developed tools for unbiased robust image registration that are extremely accurate in the presence of longitudinal change, e.g. atrophy, tumor growth, or jaw, neck, tongue movement. He has taken over primary responsibility for the ongoing development of the FreeSurfer longitudinal analysis stream, and also worked with Peter Sand to develop and validate prototype tools for registering histological and block-face images to high-resolution ex vivo MRI. His interests also include advanced methods for modeling disease progression and treatment response, as well as spectral shape analysis and other topics in computational geometry and topology. |
Personal website |
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Mert Sabuncu |
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Assistant Professor, School of Electrical & Computer Engineering Cornell University |
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PhD, Electrical Engineering, Princeton University | |
msabuncu [at] nmr.mgh.harvard.edu |
Mert's work involves cutting edge segmentation using probabilistic label fusion, and more recently has been working on imaging genetics, multivariate pattern analysis, and longitudinal statistics. |
Personal website |
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David Salat |
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Associate Professor in Radiology at Harvard Medical School Assistant in Neuroscience at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Behavioral Neuroscience, Oregon Health and Science University | |
salat [at] nmr.mgh.harvard.edu |
David's research examines structural and functional changes in the brain with aging and age-associated neurodegenerative disease. A primary focus of this work is to determine how the common decline in vascular health with advancing age contributes to neurodegenerative changes, cognitive attenuation and the development of Alzheimer’s disease and other dementias. Through these studies, we hope to advance procedures for the clinical utilization of imaging technology in the diagnosis, characterization and tracking of neurodegenerative disease as well as towards advancing understanding of the pathological mechanisms that cause dementia. |
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Dylan Tisdall |
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Assistant Professor of Radiology |
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PhD, Computing Science, Simon Fraser University, Canada | |
tisdall [at] nmr.mgh.harvard.edu |
Dylan focuses on developing novel MRI acquisition and data analysis techniques. His work includes prospectively motion-corrected MRI sequences for clinical and research anatomical studies, diffusion sequences and eddy-current measurement for high-amplitude gradient systems, and the application of statistical signal processing methods to the estimation of tissue parameters. |
Personal website |
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Research Fellows
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Chiara Maffei |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Cognitive and Brain Sciences, CIMeC Center for Mind/Brain Sciences, Trento University, Italy |
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CMAFFEI[at] mgh.harvard.edu |
Chiara is interested in the application and validation of diffusion-based tractography techniques. Tractography allows the;investigation of the complex white matter architecture. However the strong dependence of this technique on acquisition and algorithm parameters prevents the reliable investigation of some more critical brain connections. My work focuses on combining high resolution validation methods, such like optical imaging and ex-vivo MRI, to enlarge our knowledge of brain connectivity, with the ultimate goal of improving to the in-vivo tractography applications in both clinical and basic research |
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Aina Frau-Pascual |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Applied Mathematics, Inria and Grenoble-Alpes University, France |
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AFRAUPASCUAL[at] mgh.harvard.edu |
Aina works on the development of methods for diffusion and functional MRI data analysis to study brain connectivity. Previously, she worked on the development of methods for the analysis of BOLD and ASL task fMRI. Website: https://ainafp.github.io/ |
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Malte Hoffmann |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, MRI Physics, University of Cambridge, UK |
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mhoffmann [at] mgh.harvard.edu |
Malte is interested in MRI sequence development, specifically techniques that correct for subject motion as it happens in the scanner. His work includes the translation of these methods to fetal imaging, where motion is a major challenge. Malte also works on the FreeSurfer longitudinal analysis stream to improve the detection of structural changes in the brain, by which we hope to advance the early diagnosis of disease. |
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Yael Balbastre |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Medical Physics and Imaging, Paris-Saclay University |
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ybalbastre [at] mgh.harvard.edu |
Yael works on multimodal image registration and vasculature segmentation with the aim of building high-resolution cellular atlases of the brain. Before that, Yael worked on Bayesian shape modelling, segmentation, registration, and quantitative MRI at University College London. |
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Developers
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Andrew Hoopes |
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Department of Radiology, MGH | |
BS, Neuroscience, Bates College | |
ahoopes [at] mgh.harvard.edu |
Andrew works on various avenues of FreeSurfer development. His focuses include optimization, upkeep, testing, and machine learning.
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Ruopeng Wang |
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Department of Radiology, MGH | |
MS, Nuclear Engineering, MIT | |
rpwang [at] nmr.mgh.harvard.edu |
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Rob D. | |
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Department of Radiology, MGH | |
M. Sc, Electrical Engineering, Tufts University | |
Rob supports, tests and installs software for the groups that produce Freesurfer and the magnetoencephalography (MEG) software.
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Paul Wighton |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Computing Science, Simon Fraser University, Canada | |
pwighton [at] nmr.mgh.harvard.edu |
Paul's work focuses on MRI sequence development. His main focus is augmenting existing sequences to track motion prospectively using data from external sources. He also works on the theoretical and technical challenges of real-time fMRI. |
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Technical Staff
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Leah Morgan |
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Sr. Research Technologist & Project Manager |
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MS, Bioengineering, Cape Town University |
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Leah organizes scanning operations within the lab. She acquires and analyzes ex vivo brain MRI data, both structural and diffusion, at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). Leah is also Project Manager to Bruce Fischl, Doug Greve and Andre Van der Kouwe and provides administrative support for all LCN lab members. Twice a year, she organizes local FreeSurfer courses aimed at teaching members of the neuroimaging research field how to use the software. |
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Kimberly Nestor |
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Research Technician II |
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BA, Neuroscience, Wheaton College |
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Kim performs histology and anatomical analyses on human brain tissue in order to examine the histology for improved brain mapping of neurotypical brains and those with aging and preclinical Alzheimer's Disease pathology. The histochemistry protocols that Kim uses to microscopically examine brain regions are Nissl, Thioflavin S, Gallyas myelin, Sudan black, Hematoxylin and eosin. She also performs immunohistochemistry for early forms of phosphorylated tau, beta-amyloid, and other antibodies in the medial temporal lobe to better understand the pathology of aging and Alzheimer's Disease. These protocols enable the microscopic cellular study of structures such as neurons, neurofibrillary tangles, myelin, and lipofuscin, as well as extracellular structures, amyloid plaques, and blood vessels. Kim uses Freeview to identify and manually label neuroanatomical structures on ex vivo human brain tissue. The labels are used as ground truth and training data to develop computational algorithms that model the structure, volume and surfaces of the human brain. These models are incorporated in the Freesurfer package. |
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Robert Jones |
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Research Technician II |
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BA, Biological Chemistry and Mathematics, Bates College |
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Robert acquires and analyzes ex vivo brain MRI data for a project on post mortem validation of diffusion MRI. He also assists with in vivo neuroimaging data collection for the Human Connectome Project study. In addition, Robert is responsible for managing IRB human study protocols, and assists with quality assurance of imaging data and testing of image analysis algorithms. |
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Mingu Kim |
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Research Technician II |
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BA, Applied Mathematics, Harvard University |
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Mingu acquires and analyzes in vivo neuroimaging and clinical data for the Human Connectome Project study of adolescents with depression and anxiety disorders. He develops statistical methods to investigate whether neuroimaging and clinical data can be used to predict disease progression. In addition, Mingu assists with quality assurance of imaging data and testing of image analysis algorithms. |
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Holly Freeman |
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Research Technician II |
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MS, Health Psychology, University of the Sciences in Philadelphia |
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hjfreeman@mgh.harvard.edu |
Holly acquires and analyzes ex vivo brain MRI data, both structural and diffusion, at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). She also analyzes in vivo data for studies focused on clinical populations. In addition to brain imaging acquisition and analysis, Holly also assists with the testing and development of FreeSurfer, as well as teaching members of the neuroimaging research field how to use the software at local and international courses. |
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Matt Vera |
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Research Technician II |
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MS, Medical Science, Boston University Graduate School of Medicine |
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mvera2@mgh.harvard.edu |
Matt acquires and analyzes ex vivo brain MRI data, both structural and diffusion, at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). He also analyzes in vivo data for studies focused on clinical populations. In addition to brain imaging acquisition and analysis, Matt also assists with the testing and development of FreeSurfer, as well as teaching members of the neuroimaging research field how to use the software at local and international courses. |
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Devani Cordero |
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Data Analyst I Intern Supervisor |
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BA, Psychology, Gordon College |
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dccordero@mgh.harvard.edu |
Devani acquires and analyzes ex vivo brain MRI data, both structural and diffusion, at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). She also analyzes in vivo data for studies focused on clinical populations. In addition to brain imaging acquisition and analysis, Devani also assists with the testing and development of FreeSurfer, as well as teaching members of the neuroimaging research field how to use the software at local and international courses. |
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Emily Williams |
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Research Technician II |
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BA, Neuroscience, Hamilton College |
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ewilliams36@mgh.harvard.edu |
Emily performs histology and anatomical analyses on human brain tissue in order to examine the histology for improved brain mapping of neurotypical brains and those with aging and preclinical Alzheimer's Disease pathology. The histochemistry protocols that Emily uses to microscopically examine brain regions are Nissl, Thioflavin S, and Gallyas myelin. She also uses Freeview to identify and manually label neuroanatomical structures on ex vivo human brain tissue. The labels are used as ground truth and training data to develop computational algorithms that model the structure, volume and surfaces of the human brain. These models are incorporated in the Freesurfer package. |
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Natalya Slepneva |
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Research Technician II |
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nslepneva@mgh.harvard.edu |
Natalya performs histology and anatomical analyses on human brain tissue in order to examine the histology for improved brain mapping of neurotypical brains and those with aging and preclinical Alzheimer's Disease pathology. The histochemistry protocols that Natalya uses to microscopically examine brain regions are Nissl, Thioflavin S, and Gallyas myelin. She also uses Freeview to identify and manually label neuroanatomical structures on ex vivo human brain tissue. The labels are used as ground truth and training data to develop computational algorithms that model the structure, volume and surfaces of the human brain. These models are incorporated in the Freesurfer package. |
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Jocelyn Mora |
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Research Technician I |
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BA, Neuroscience, Wheaton College, MA |
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jsmora@mgh.harvard.edu |
Jocelyn acquires and analyzes ex vivo brain MRI data, both structural and diffusion, at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). She also analyzes in vivo data for studies focused on clinical populations. In addition to brain imaging acquisition and analysis, Jocelyn also assists with the testing and development of FreeSurfer, as well as teaching members of the neuroimaging research field how to use the software at local and international courses. |
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Students
Alumni
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Viviana Siles |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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viliess [at] mgh.harvard.edu |
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Matt Larrabee |
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Research Technician II |
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BS, Psychology, University of Massachusetts Boston |
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mlarrabee1@mgh.harvard.edu |
Matt acquires and analyzes ex vivo brain MRI data, both structural and diffusion, at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). He also analyzes in vivo data for studies focused on clinical populations. In addition to brain imaging acquisition and analysis, Mattialso assists with the testing and development of FreeSurfer, as well as teaching members of the neuroimaging research field how to use the software at local and international courses. |
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Bram Diamond |
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Sr. Clinical Research Coordinator |
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BS, Brain and Cognitive Sciences, University of Rochester |
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Bram acquires and analyzes ex vivo brain MRI data, both structural and diffusion, at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). He also analyzes in vivo data for studies focused on clinical populations, including traumatic brain injury (TBI) and epilepsy. In addition to brain imaging acquisition and analysis, Bram manages the lab’s IRB regulatory documents. He also assists with the testing and development of FreeSurfer, as well as teaching members of the neuroimaging research field how to use the software at local and international courses. |
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Jieyu Jenny Cheng |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Department of Electronic Engineering, City University of Hong Kong, Hong Kong |
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jcheng21[at] mgh.harvard.edu |
Jieyu works on surface and volumetric registration of brain MRI images. She is currently focused on the development of longitudinal processing pipeline for young children and the quantification of reconstructed brain surfaces. She is also interested in image segmentation and volumetric registration using deep learning. |
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Emma Boyd |
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Research Technician II |
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BS, Biopsychology, Tufts University |
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Emma acquires and analyzes ex vivo brain MRI data, both structural and diffusion, at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). She also analyzes in vivo data for studies focused on clinical populations. In addition to brain imaging acquisition and analysis, Emma also assists with the testing and development of FreeSurfer, as well as teaching members of the neuroimaging research field how to use the software at local and international courses. |
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Amod Jog |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Johns Hopkins University, Baltimore, USA | |
AJOG[at] mgh.harvard.edu |
Amod works on image synthesis approaches to reduce the bias and variance in analysis results introduced due to MR scanner differences. He has previously worked on biological motion analysis using MRI, image segmentation, and image super-resolution. His general interests include computer vision and machine learning. Website: https://asjog.github.io/ |
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Isik Karahanoglu |
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Instructor in Neurology, Department of Neurology, Massachusetts General Hospital | |
fkarahanoglu [at] mgh.harvard.edu |
Isik focuses on developing new methods for fMRI and EEG data analysis. She is currently investigating motion-related artifacts, and functional and structural connectivity measures, especially in minimally verbal children with autism, using fMRI and DWI. |
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Giorgia Grisot |
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PhD candidate, Harvard-MIT HST program | |
ggrisot [at] partners.org |
My work mostly focuses on validation of diffusion MRI tractography. Specifically, I use a multimodal approach that links chemical tracing in non-human primates to diffusion MRI in humans to validate, map and characterize critical connections of the human brain. |
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Emily Lindemer |
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PhD, Harvard-MIT HST program | |
lindemer [at] mit.edu |
Emily works on automatic segmentation procedures for white matter lesions to be included in FreeSurfer releases. In addition to the segmentation process, she develops new methods of analyzing the qualitative changes of white matter within lesions using multimodal MRI. She is interested in relating these changes to cerebrovascular integrity, particularly in the context of aging and cognitive decline as it leads to Alzheimer's disease. |
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Nick Schmansky |
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Department of Radiology, MGH | |
MA, Cognitive and Neural Systems, Boston University MSc, Artificial Intelligence, University of Edinburgh |
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nicks [at] nmr.mgh.harvard.edu |
Nick has been the lead software engineer for many years, and is responsible for taking FreeSurfer from a loosely organized set of binaries and turning it into a well-documented, extensively tested, easy to install and useful suite of tools. |
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Ani Varjabedian |
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Department of Radiology, MGH | |
BS, Zoology, University of Maine, Orono | |
aniv [at] nmr.mgh.harvard.edu |
Ani is mainly involved ex vivo brain imaging, but also helps out with in vivo studies as well. She acquires and analyzes both structural and diffusion MRI data at a variety of resolutions (100um-1mm) and field strengths (7T, 3T, 1.5T). She also acquires optical coherence tomography (OCT) data and performs histology to help fully characterize the brain tissue. In addition to her scanning and wet-lab responsibilities, Ani also assists with the testing and development of the FreeSurfer software.
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Louis Vinke |
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Department of Radiology, MGH | |
MA, Experimental Psychology, Bowling Green State University | |
vinke [at] nmr.mgh.harvard.edu |
Louis is involved in high resolution (4.7T & 7T) and low resolution (1.5T) ex vivo brain imaging, as well as in vivo imaging at 3T. He also assists with the testing and development of FreeSurfer, and is working on developing tools to help QA large datasets processed with FreeSurfer. Lastly, he maintains the lab website and helps out in the biochemistry lab. |
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Christian Wachinger |
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Research Fellow in Neurology at Harvard Medical School Research Fellow at the Computer Science and Artificial Intelligence Lab, MIT |
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PhD, Technische Universität München, Germany | |
wachinge [at] nmr.mgh.harvard.edu |
Christian currently works on BrainPrint, a discriminative characterization of brain morphology. BrainPrint permits the computation of similarities between brains. Applications include the identification of subjects by their brain and the diagnosis of Alzheimer’s disease. Christian also works on image segmentation and robust multi-modal registration. |
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Stefano Pedemonte |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Medical Physics and Bioeng. UCL, London MSc, Information Eng., Politecnico Di Milano, Italy |
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spedemonte [at] mgh.harvard.edu |
Stefano's work focuses on tomographic acquisition and image formation. He develops acquisition and reconstruction techniques for dynamic, motion-aware Positron Emission Tomography, Magnetic Resonance and Single Photon Emission Computed Tomography. He is the ideator of the software occiput.io. |
Personal website |
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Tong Tong |
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Research Fellow in Radiology at Harvard Medical School Research Fellow at Massachusetts General Hospital Department of Radiology, MGH |
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PhD, Computing, Imperial College London, UK | |
ttong2 [at] mgh.harvard.edu |
Tong's research interest focuses on brain image analysis and machine learning techniques. His current work is to develop algorithms for laminar modelling using ultra-high resolution ex vivo MRI and optical coherence tomography (OCT) images. |
Personal website |
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Dorit Kliemann |
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Research Fellow in Neurology, Department of Neurology, Massachusetts General Hospital | |
dorit [at] mit.edu |
Dorit is a postdoctoral research fellow interested in how humans process social information in the brain, using a multi-methodal approach, including behavioral and eye-tracking measures, structural and functional neuroimaging, as well as diffusion weighted imaging to investigate connectivity patterns. Her research at LCN mainly investigates amygdalar nuclei specific function (e.g., resting state pattern), shape and structure (e.g., high-res ex-vivo data) in neurotypically developed individuals as well as individuals with ASD |
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Tian Ge |
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Research Fellow at Massachusetts General Hospital | |
PhD, Computer Science, University of Warwick, UK | |
tge1 [at] mgh.harvard.edu |
Tian works primarily on developing novel mathematical models and statistical approaches for neuroimging data analysis and computational imaging genetics. |
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- Laboratory for Computational Neuroimaging • 149 Thirteenth Street, Rm 2301, Charlestown, MA 02129 -