Woodruff School of Mechanical Engineering

NRE 8011/8012 and MP 6011/6012 Seminar

Nuclear & Radiological Engineering and Medical Physics Programs


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


Dr. Hao Gao


Emory University


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


Boggs Building, Room 3-47


Dr. Lei Zhu


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.


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.