Frequency Diffeomorphisms for Fast Image Registration
Brown Bag Lecture by Dr. Brown Bag Lecture by Dr. Miaomiao Zhang | 9/19/2017 11:00AM – 11:30AM | 7th Floor Conference Room, Bldg 38A
Large deformation diffeomorphic metric mapping (LDDMM) has been widely used in the field of image registration, atlas-based image segmentation, and anatomical shape analysis. However, the extremely high computational cost and large memory footprint of the current implementations of LDDMM have limited its applicability in important areas that require computational efficiency. In this talk, I will introduce a novel finite dimensional Fourier representation of diffeomorphisms that dramatically speeds up the state-of-the-art diffeomorphic image registration methods while producing equally accurate alignment. Two different applications of image registration are demonstrated: neuroimaging and in-utero imaging.
Miaomiao Zhang is an assistant professor in the Computer Science and Engineering at Lehigh University. Her research work focuses on developing novel models at the intersection of statistics, mathematics, and computer engineering in the field of medical and biological imaging. Before joining Lehigh University, Miaomiao completed her Ph.D. degree in Computer Science at University of Utah under the supervision of Dr. Tom Fletcher. After that, she worked with Dr. Polina Golland as a postdoctoral associate at Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. She received the MICCAI Young Scientist Award 2014 and was a runner-up for Young Scientist Award 2016.