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JCCC Member Directory

Michael McNitt-Gray, Ph.D.
Michael McNitt-Gray, Ph.D.

Affiliation(s):

Professor in Residence, Department of Radiological Sciences
Director, Biomedical Physics Interdepartmental Graduate Program
Member, JCCC Cancer Molecular Imaging Program Area

Contact Information:

Phone:
(310) 794-8979
Email:
Website:

Scientific Interest(s):

Dr. Michael McNitt-Gray's research focuses on the use of X-ray Computed Tomography (CT) imaging physics and advanced computer processing techniques for the early detection and characterization of disease. The CT imaging physics studies include methods to assess and improve the image quality of CT images as well as methods to accurately assess the radiation dose from CT imaging. The image processing studies include methods to automatically identify normal and pathological regions within an image as well as methods to identify characteristics from the image data that will help identify whether suspicious objects identified within the image are cancerous or not. If methods can be developed to distinguish cancers from benign structures based on image characteristics, then more invasive and expensive diagnostic tests can be avoided or reduced.

Selected Cancer-Related Publications:

Armato SG, McLennan G, Hawkins D, Bidaut L, McNitt-Gray MF, Meyer CR, Reeves AP, Zhao B, Aberle DR, Henschke CI, Hoffman EA, Kazerooni EA, MacMahon H, Van Beeke EJ, Yankelevitz D, Biancardi AM, Bland PH, Brown MS, Engelmann RM, Laderach GE, Max D, Pais RC, Qing DP, Roberts RY, Smith AR, Starkey A, Batrah P, Caligiuri P, Farooqi A, Gladish GW, Jude CM, Munden RF, Petkovska I, Quint LE, Schwartz LH, Sundaram B, Dodd LE, Fenimore C, Gur D, Petrick N, Freymann J, Kirby J, Hughes B, Casteele AV, Gupte S, Sallamm M, Heath MD, Kuhn MH, Dharaiya E, Burns R, Fryd DS, Salganicoff M, Anand V, Shreter U, Vastagh S, Croft BY, Clarke LP. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys. 2011 Feb;38(2):915-31.

Buckler AJ, Schwartz LH, Petrick N, McNitt-Gray M, Zhao B, Fenimore C, Reeves AP, Mozley PD, Avila RS. Data sets for the qualification of volumetric CT as a quantitative imaging biomarker in lung cancer. Opt Express. 2010 Jul 5;18(14):15267-82.

Turner AC, Zankl M, DeMarco JJ, Cagnon CH, Zhang D, Angel E, Cody DD, Stevens DM, McCollough CH, McNitt-Gray MF. The feasibility of a scanner-independent technique to estimate organ dose from MDCT scans: using CTDIvol to account for differences between scanners. Med Phys. 2010 Apr;37(4):1816-25.

Meyer CR, Armato SG, Fenimore CP, McLennan G, Bidaut LM, Barboriak DP, Gavrielides MA, Jackson EF, McNitt-Gray MF, Kinahan PE, Petrick N, Zhao B. Quantitative imaging to assess tumor response to therapy: common themes of measurement, truth data, and error sources. Transl Oncol. 2009 Dec;2(4):198-210.

McNitt-Gray MF, Armato SG, Meyer CR, Reeves AP, McLennan G, Pais RC, Freymann J, Brown MS, Engelmann RM, Bland PH, Laderach GE, Piker C, Guo J, Towfic Z, Qing DP, Yankelevitz DF, Aberle DR, van Beek EJ, MacMahon H, Kazerooni EA, Croft BY, Clarke LP. The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation. Acad Radiol. 2007 Dec;14(12):1464-74.