Persistent Homology in Sparse Regression and Its Application to Brain Morphometry. IEEE Trans Med Imaging 2015 Sep;34(9):1928-39
Date
03/31/2015Pubmed ID
25823032Pubmed Central ID
PMC4629505DOI
10.1109/TMI.2015.2416271Scopus ID
2-s2.0-84940907482 (requires institutional sign-in at Scopus site) 54 CitationsAbstract
Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult problem in learning the sparse system. In this paper, by treating the the tuning parameter as an additional dimension, persistent homological structures over the parameter space is introduced and explored. The structures are then further exploited in drastically speeding up the computation using the proposed soft-thresholding technique. The topological structures are further used as multivariate features in the tensor-based morphometry (TBM) in characterizing white matter alterations in children who have experienced severe early life stress and maltreatment. These analyses reveal that stress-exposed children exhibit more diffuse anatomical organization across the whole white matter region.
Author List
Chung MK, Hanson JL, Ye J, Davidson RJ, Pollak SDAuthor
Jamie Hanson PhD Associate Professor in the Pediatrics department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AdolescentBrain
Brain Mapping
Child
Child Abuse
Diffusion Tensor Imaging
Female
Humans
Image Processing, Computer-Assisted
Male
Stress, Psychological
