News Category
Prefrontal-Thalamic anatomical connectivity and executive cognitive function in schizophrenia
Oct. 2, 2017—Monica Giraldo-Chica, Baxter P. Rogers, Stephen M. Damon, Bennett A. Landman, Neil D. Woodward. “Prefrontal-Thalamic anatomical connectivity and executive cognitive function in schizophrenia.” Biological Psychiatry, September 2017. http://dx.doi.org/10.1016/j.biopsych.2017.09.022 Full text: http://www.biologicalpsychiatryjournal.com/article/S0006-3223(17)32010-3/fulltext NIHMSID Abstract Background Executive cognitive functions, including working memory, cognitive flexibility, and inhibition, are impaired in schizophrenia. Executive functions rely on coordinated information processing...
Neurite orientation dispersion and density imaging (NODDI) of the prefrontal cortex in psychosis
Feb. 8, 2017—“Neurite orientation dispersion and density imaging (NODDI) of the prefrontal cortex in psychosis” Authors: Neil D. Woodward, Prasanna Parvatheni, Baxter Rogers, Stephen Damon, Bennett Landman. Society of Biological Psychiatry 2017 (SoBP) Healthy>Psychosis results in ODI
Dendritic organization within the PFC measured in vivo in psychosis using neurite orientation dispersion and density imaging (NODDI)
Feb. 4, 2017—“Dendritic organization within the PFC measured in vivo in psychosis using neurite orientation dispersion and density imaging (NODDI)” Authors: Neil D. Woodward1, Prasanna Parvatheni2, Baxter Rogers3, Stephen Damon2, Bennett Landman2 .1 Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine 2 School of Engineering, Vanderbilt University 3 Vanderbilt University Institute of Imaging Sciences...
Comparison of Multi-Fiber Reproducibility of PAS-MRI and Q-ball With Empirical Multiple b-Value HARDI
Feb. 3, 2017—Vishwesh Nath, Kurt G. Schilling, Justin Blaber, Zhaohua Ding, Adam W. Anderson, Bennett A Landman. “Comparison of Multi-Fiber Reproducibility of PAS-MRI and Q-ball With Empirical Multiple b-Value HARDI ” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2017. Oral presentation. Full Text: Abstract Crossing fibers are prevalent in human brains and a...
Multi-Atlas Spleen Segmentation on CT Using Adaptive Context Learning
Feb. 3, 2017—Jiaqi Liu, Yuankai Huo, Zhoubing Xu, Albert Assad, Richard G. Abramson, Bennett A. Landman. “Multi-Atlas Spleen Segmentation on CT Using Adaptive Context Learning” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2017. Oral presentation. Full Text: Abstract Multi-atlas segmentation has shown to be a promising approach for spleen segmentation. To deal with...
Multi-Scale Hippocampal Parcellation Improves Atlas-Based Segmentation Accuracy
Feb. 3, 2017—Andrew J. Plassard, Maureen McHugo, Stephan Heckers, Bennett A. Landman. “Multi-Scale Hippocampal Parcellation Improves Atlas-Based Segmentation Accuracy” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2017. Full Text: Abstract The hippocampus is one of the most studied regions of the brain. Recent advances in MRI have produced high-contrast imaging of the hippocampus....
Peripheral sphingolipids are associated with variation in white matter microstructure in older adults.
Jul. 31, 2016—Christopher E. Gonzalez, Vijay K. Venkatraman, Yang An, Bennett A. Landman, Christos Davatzikos, Veera Venkata Ratnam Bandaru, Norman J. Haughey, Luigi Ferruci, Michelle M. Mielke, Susan M. Resnick. “Peripheral sphingolipids are associated with variation in white matter microstructure in older adults.” Neurobiology of Aging. July 2016. Volume 43, Pages 156–163 Full Text: https://www.ncbi.nlm.nih.gov/pubmed/27255825 Abstract Sphingolipids...
Deep Learning for Brain Tumor Classification
Jul. 1, 2016—Justin S. Paul, Andrew J. Plassard, Bennett A. Landman, Daniel Fabbri. “Deep Learning for Brain Tumor Classification.” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2017. Oral presentation. Abstract Recent research has shown that deep learning methods have performed well on supervised machine learning, image classification tasks. The purpose of this study is...
Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment
Jan. 31, 2016—Robert L. Harrigan, Benjamin C. Yvernault, Brian D. Boyd, Stephen M. Damon, Kyla David Gibney, Benjamin N. Conrad, Nicholas S. Phillips, Baxter P. Rogers, Yurui Gao, Bennett A. Landman “Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment” Neuroimage, 2014. In press May 2015† Full Text:...
Integration of the Java Image Science Toolkit with E-Science Platform
Jan. 31, 2016—S. Damon, S. Panjwani, S. Bao, P. Kochunov, B. Landman, Integration of the Java Image Science Toolkit with E-Science Platform. 2016. InSight Journal. #963 Full text: http://insight-journal.org/browse/publication/963 Abstract Medical image analyses rely on diverse software packages assembled into a “pipeline”. The Java Image Science Toolkit (JIST) has served as a standalone plugin into the Medical...