This is a competing renewal application for a multidisciplinary pre-doctoral training program at Stanford University in biomedical imaging technologies. Our mission is to train the next generation of researchers in and inventors of biomedical imaging technology. Imaging technology continues to evolve at a rapid pace generating new techniques that will become the powerful research tools and the standard of clinical care for tomorrow. There is a high need for trained researchers in this field to fill positions in academia, industry, and government. Stanford University has a unique multidisciplinary research effort in biomedical imaging and a track record of innovation spanning magnetic resonance, computed tomography and radiography, ultrasound, PET, optical, and hybrid imaging such as X-ray/MR and PET/MR, as well as image processing and analysis for diagnosis, radiation therapy, and basic science. The training program will draw and fund students from 5 different degree granting programs to train in biomedical imaging technology with faculty from 9 different departments. The main need is funding for the early years of a student's training. Four new students will be recruited each year; each funded for two years of their considerably longer PhD programs.

Public Health Relevance

Our mission is to train the next generation of researchers in and inventors of biomedical imaging technology. Imaging technology continues to evolve at a rapid pace generating new techniques that will become the powerful research tools and the standard of clinical care for tomorrow. There is a high need for trained researchers in this field to fill positions in academia, industry, and government.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Institutional National Research Service Award (T32)
Project #
5T32EB009653-09
Application #
9554912
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Erim, Zeynep
Project Start
2009-07-01
Project End
2020-08-31
Budget Start
2018-09-01
Budget End
2019-08-31
Support Year
9
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Stanford University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Loewke, Nathan O; Pai, Sunil; Cordeiro, Christine et al. (2018) Automated Cell Segmentation for Quantitative Phase Microscopy. IEEE Trans Med Imaging 37:929-940
Krajina, Brad A; Tropini, Carolina; Zhu, Audrey et al. (2017) Dynamic Light Scattering Microrheology Reveals Multiscale Viscoelasticity of Polymer Gels and Precious Biological Materials. ACS Cent Sci 3:1294-1303
Dwork, Nicholas; Lasry, Eric M; Pauly, John M et al. (2017) Formulation of image fusion as a constrained least squares optimization problem. J Med Imaging (Bellingham) 4:014003
Smith, Gennifer T; Dwork, Nicholas; Khan, Saara A et al. (2016) Robust dipstick urinalysis using a low-cost, micro-volume slipping manifold and mobile phone platform. Lab Chip 16:2069-78
Marx, Michael; Butts Pauly, Kim (2016) Improved MRI thermometry with multiple-echo spirals. Magn Reson Med 76:747-56
Maute, Roy L; Gordon, Sydney R; Mayer, Aaron T et al. (2015) Engineering high-affinity PD-1 variants for optimized immunotherapy and immuno-PET imaging. Proc Natl Acad Sci U S A 112:E6506-14
Savall, Joan; Ho, Eric Tatt Wei; Huang, Cheng et al. (2015) Dexterous robotic manipulation of alert adult Drosophila for high-content experimentation. Nat Methods 12:657-660
Smith, Gennifer T; Dwork, Nicholas; O'Connor, Daniel et al. (2015) Automated, Depth-Resolved Estimation of the Attenuation Coefficient From Optical Coherence Tomography Data. IEEE Trans Med Imaging 34:2592-602
Marx, Michael; Plata, Juan; Pauly, Kim Butts (2015) Toward volumetric MR thermometry with the MASTER sequence. IEEE Trans Med Imaging 34:148-55
Bieniosek, M F; Olcott, P D; Levin, C S (2013) Readout strategy of an electro-optical coupled PET detector for time-of-flight PET/MRI. Phys Med Biol 58:7227-38

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