The image registration core will perform research and development that support the broad range of image registration activities in Projects 1-3. The core will develop methods of image registration that can meet the stringent requirements of the projects in this proposal: fast computation, high spatial resolution, motion estimation, and management of uncertainty and registration error. Core B will develop software for the projects in the following areas: mapping histology back to in vivo image volumes (Project 1);estimating head motion for EPI speech activation studies (Project 2);and registering dynamic contrast enhanced (DCE) MRI breast volumes (Project 3). A general cross-cutting aim will be to quantify and predict registration uncertainty for the image registration algorithms used in the Projects.

Public Health Relevance

? This core will design state-of-the-art image registration software that will be applied to the management of cancer patient therapy. ,

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA087634-10
Application #
8445396
Study Section
Special Emphasis Panel (ZCA1-GRB-P)
Project Start
Project End
2015-02-28
Budget Start
2013-03-01
Budget End
2014-02-28
Support Year
10
Fiscal Year
2013
Total Cost
$202,499
Indirect Cost
$64,964
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Olafsson, Valur T; Noll, Douglas C; Fessler, Jeffrey A (2018) Fast Spatial Resolution Analysis of Quadratic Penalized Least-Squares Image Reconstruction With Separate Real and Imaginary Roughness Penalty: Application to fMRI. IEEE Trans Med Imaging 37:604-614
Nyati, Shyam; Young, Grant; Ross, Brian Dale et al. (2017) Quantitative and Dynamic Imaging of ATM Kinase Activity. Methods Mol Biol 1596:131-145
Nyati, Shyam; Young, Grant; Ross, Brian Dale et al. (2017) Quantitative and Dynamic Imaging of ATM Kinase Activity by Bioluminescence Imaging. Methods Mol Biol 1599:97-111
Nataraj, Gopal; Nielsen, Jon-Fredrik; Fessler, Jeffrey A (2017) Optimizing MR Scan Design for Model-Based ${T}_{1}$ , ${T}_{2}$ Estimation From Steady-State Sequences. IEEE Trans Med Imaging 36:467-477
Jintamethasawat, Rungroj; Zhang, Xiaohui; Carson, Paul L et al. (2017) Acoustic beam anomalies in automated breast imaging. J Med Imaging (Bellingham) 4:045001
Nataraj, Gopal; Nielsen, Jon-Fredrick; Fessler, Jeffrey (2016) Optimizing MR Scan Design for Model-Based T1, T2 Estimation from Steady-State Sequences. IEEE Trans Med Imaging :
Larson, Eric D; Lee, Won-Mean; Roubidoux, Marilyn A et al. (2016) Automated Breast Ultrasound: Dual-Sided Compared with Single-Sided Imaging. Ultrasound Med Biol 42:2072-82
Piert, Morand; Montgomery, Jeffrey; Kunju, Lakshmi Priya et al. (2016) 18F-Choline PET/MRI: The Additional Value of PET for MRI-Guided Transrectal Prostate Biopsies. J Nucl Med 57:1065-70
Keith, Lauren; Ross, Brian D; Galbán, Craig J et al. (2016) Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping. Tomography 2:267-275
Berisha, Visar; Wisler, Alan; Hero, Alfred O et al. (2016) Empirically Estimable Classification Bounds Based on a Nonparametric Divergence Measure. IEEE Trans Signal Process 64:580-591

Showing the most recent 10 out of 92 publications