David N. Kennedy, Ph.D.
Neuroscience Center at Massachusetts General Hospital

Massachusetts General Hospital – East
Building 149
13th Street
Charlestown, MA 02129

Telephone: 617-726-5621
E-mail: dave@cma.mgh.harvard.edu


Biography
Dr. Kennedy received his BS in Physics from the University of Rochester and MS and PhD in Nuclear Engineering from the Massachusetts Institute of Technology, Cambridge. He came to the MGH in 1988.

Research Program
The research efforts in the Kennedy laboratory are in the areas of MRI-based morphometric neuroanatomic analysis, functional MRI and diffusion tensor pathway analysis for both the study of normal development and, through numerous collaborative efforts, alterations in various clinical populations including stroke, schizophrenia, autism, Huntington's Disease and Alzheimer’s Disease. This laboratory is extending previously developed pixel segmentation and morphological quantification methods, continuing the efforts to develop a unified neuroanatomic segmentation framework and transition these tools to clinical applications on a routinely available software platform.

Dr. Kennedy is also actively involved in the development of neuroinformatics resources such as the Internet Brain Volumetric Database, Internet Brain Segmentation Repository, and the Image Analysis Tools Registry. This laboratory is continuing previously developed methods to characterize shape and shape change metrics in normal subjects and pathological patient populations and disseminating segmentation tools and comparison methods, as well as the results of image segmentation and volumetric analysis to the community as a whole using the World Wide Web.

A unified framework for segmentation and classification in support of a neurologically-based anatomic morphology has emerged. This unified framework incorporates the multispectral nature of MRI data. This framework intrinsically includes estimates of the underlying uncertainty associated with the segmentation and classification process, which supports a rational assessment of sensitivity of a given method. This approach expands upon traditional "static" image analysis by incorporation of shape-based analysis for anomaly detection.

In addition, Dr. Kennedy’s group has identified a number of clinical application areas, which, in addition to fostering enhanced analytic capabilities to studies in these areas, permits optimization of the operational efficiency of the resulting analysis. Specifically, the segmentation, classification and shape analysis of MRI data in patients with stroke and Huntington's disease, as well as the appropriate normative populations, provide a vital test-bed for the evaluation of the clinical utility of these morphological analysis techniques.

Publications
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• Faraone SV, Seidman LJ, Kremen WS, Kennedy D, Makris N, Caviness VS, Goldstein J, Tsuang MT. Structural brain abnormalities among relatives of patients with schizophrenia: implications for linkage studies. Schizophr Res, Apr 1;60(2-3):125-40, 2003.
  
• Rauch SL, Phillips KA, Segal E, Makris N, Shin LM, Whalen PJ, Jenike MA, Caviness VS, Jr, Kennedy DN. A preliminary morphometric magnetic resonance imaging study of regional brain volumes in body dysmorphic disorder. Psychiatry Res, Jan 20;122(1):13-9, 2003.
  
• Desai M, Mangoubi R, Shah J, Karl W, Pien H, Worth A, Kennedy D. Functional MRI activity characterization using response time shift estimates from curve evolution. IEEE Trans Med Imaging, Nov;21(11):1402-12, 2002.
  
• Caviness VS, Makris N, Montinaro E, Sahin NT, Bates JF, Schwamm L, Caplan D, Kennedy DN. Anatomy of stroke, Part I: an MRI-based topographic and volumetric System of analysis. Stroke, Nov;33(11):2549-56, 2002.
  
• Caviness VS, Makris N, Montinaro E, Sahin NT, Bates JF, Schwamm L, Caplan D, Kennedy DN. Anatomy of stroke, Part II: volumetric characteristics with implications for the local architecture of the cerebral perfusion system. Stroke, Nov;33(11):2557-64, 2002.
  
• Kennedy, DN., Makris, N., Herbert, M. R., Takahashi, T., Caviness, V. S. Basic principles of MRI and morphometry studies of human brain development. Developmental Science, 5(3), 268-278, 2002.