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Biomedical Engineering and Bioengineering Commons™
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- Aged (1)
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- Aging (1)
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- Brain imaging genetics (1)
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Articles 1 - 2 of 2
Full-Text Articles in Biomedical Engineering and Bioengineering
Pattern Discovery In Brain Imaging Genetics Via Scca Modeling With A Generic Non-Convex Penalty, Lei Du, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, Charles D. Smith, Gregory Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad
Pattern Discovery In Brain Imaging Genetics Via Scca Modeling With A Generic Non-Convex Penalty, Lei Du, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, Charles D. Smith, Gregory Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad
Neurology Faculty Publications
Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose ℓ1-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the ℓ1-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce …
White Matter Hyperintensity Associations With Cerebral Blood Flow In Elderly Subjects Stratified By Cerebrovascular Risk, Ahmed A. Bahrani, David K. Powell, Guoqiang Yu, Eleanor S. Johnson, Gregory A. Jicha, Charles D. Smith
White Matter Hyperintensity Associations With Cerebral Blood Flow In Elderly Subjects Stratified By Cerebrovascular Risk, Ahmed A. Bahrani, David K. Powell, Guoqiang Yu, Eleanor S. Johnson, Gregory A. Jicha, Charles D. Smith
Biomedical Engineering Faculty Publications
Objective: This study aims to add clarity to the relationship between deep and periventricular brain white matter hyperintensities (WMHs), cerebral blood flow (CBF), and cerebrovascular risk in older persons. Methods: Deep white matter hyperintensity (dWMH) and periventricular white matter hyperintensity (pWMH) and regional gray matter (GM) and white matter (WM) blood flow from arterial spin labeling were quantified from magnetic resonance imaging scans of 26 cognitively normal elderly subjects stratified by cerebrovascular disease (CVD) risk. Fluidattenuated inversion recovery images were acquired using a high-resolution 3-dimensional (3-D) sequence that reduced partial volume effects seen with slicebased techniques. Results: dWMHs but not …