Woodruff School of Mechanical Engineering

NRE 8011/8012 and MP 6011/6012 Seminar

Nuclear & Radiological Engineering and Medical Physics Programs

Title:

Tensor Framelet based Novel Reconstruction Methods for Better and Faster CT Imaging

Speaker:

Dr. Hao Gao

Affiliation:

Emory University

When:

Thursday, April 11, 2013 at 11:00:00 AM

Where:

Boggs Building, Room 3-47

Host:

Dr. Lei Zhu
lei.zhu@me.gatech.edu
404-385-3882

Abstract

This talk will attempt to address the following two questions: (Q1) 'Better' Imaging: provided with the same CT sinogram, can we develop new reconstruction method to further improve the state-of-art image quality? (Q2) 'Faster' Imaging: under the similar image quality standard, can we fully explore the new method for faster CT imaging, in terms of (1) faster undersampled 3D/4D data acquisition, and (2) faster image reconstruction speed that is clinically usable? A key is (A1) the use of L1-type iterative reconstruction method based on tensor framelet (TF). Another critical component for developing fast clinically-usable reconstruction is (A2) the rapid parallel algorithm for computing X-ray transform and its adjoint (O(1) per parallel thread). Then we will move on to (A3) the super-resolution technique for spiral CT to enhance axial image resolution and reduce axial partial volume artifacts, (A4) fused Analytical and Iterative Reconstruction (AIR) method as a general framework to fuse analytical reconstruction method and iterative method, and (A5) adaptive TF Technique for 4D imaging.


Biography

Dr. Hao Gao is an Assistant Professor in the Departments of Mathematics & Computer Science and Radiology & Imaging Sciences at Emory University. Dr. Hao Gao received his Ph.D. in Computational Mathematics from University of California, Irvine in 2010. His research Interests are in: Biomedical Imaging (e.g., Computed Tomography, Magenetic Resonance Imaging, Optical Imaging and Multi-modality Imaging); Signal/Image Processing (e.g., Registration, Segmentation, Video, Learning, Wavelets and Restoration); Numerical Analysis, Scientific Computing, Optimization, Compressive Sensing and Inverse Problems.