Whole Abdominal Wall Segmentation using Augmented Active Shape Models (AASM) with Multi-Atlas Label Fusion and Level Set
Feb. 1, 2016—Zhoubing Xu, Rebeccah B. Baucom, Richard G. Abramson, Benjamin K. Poulose, Bennett A. Landman, “Whole Abdominal Wall Segmentation using Augmented Active Shape Models (AASM) with Multi-Atlas Label Fusion and Level Set”, In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2016. Oral presentation. Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4845968/ Abstract The abdominal wall is an...
Disambiguating the Optic Nerve from the Surrounding Cerebrospinal Fluid: Application to MS-related Atrophy
Jan. 31, 2016—Robert L. Harrigan, Andrew J. Plassard, Frederick W. Bryan, Gabriela Caires, Louise A. Mawn, Lindsey M. Dethrage, Siddharama Pawate, Robert L. Galloway, Seth A. Smith, Bennett A. Landman. “Disambiguating the Optic Nerve from the Surrounding Cerebrospinal Fluid: Application to MS-related Atrophy.” Magnetic Resonance in Medicine. In press 2014.” Full Text: https://www.ncbi.nlm.nih.gov/pubmed/25754412 Abstract PURPOSE: Our goal...
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...
Multi-atlas Learner Fusion: An efficient segmentation approach for large-scale data
Dec. 26, 2015—Andrew J. Asman, Yuankai Huo, Andrew J. Plassard, and Bennett A. Landman, “Multi-atlas Learner Fusion: An efficient segmentation approach for large-scale data”, Medical Image Analysis (MedIA), 2015 Dec;26(1):82-91. Full text: http://linkinghub.elsevier.com/retrieve/pii/S1361-8415(15)00135-8 Abstract We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on...
Quantitative CT Imaging of Ventral Hernias: Preliminary Validation of an Anatomical Labeling Protocol
Oct. 31, 2015—Zhoubing Xu, Andrew J. Asman, Rebeccah Baucom, Richard G Abramson, Benjamin K. Poulose, and Bennett A. Landman. “Quantitative CT Imaging of Ventral Hernias: Preliminary Validation of an Anatomical Labeling Protocol.” PLoS ONE. 2015 Oct 28;10(10):e0141671. Full Text: https://www.ncbi.nlm.nih.gov/pubmed/26509450 Abstract OBJECTIVE: We described and validated a quantitative anatomical labeling protocol for extracting clinically relevant quantitative parameters for...
Data-driven Probabilistic Atlases Capture Whole-brain Individual Variation
Oct. 4, 2015—Yuankai Huo, Katherine Swett, Susan M. Resnick, Laurie E. Cutting, Bennett A. Landman. “Data-driven Probabilistic Atlases Capture Whole-brain Individual Variation”, MICCAI MAPPING Workshop, Munich, Germany, October 2015. Full text: https://www.researchgate.net/publication/303483865_Data-driven_Probabilistic_Atlases_Capture_Whole-brain_Individual_Variation Abstract
Efficient Multi-Atlas Abdominal Segmentation on Clinically Acquired CT with SIMPLE Context Learning
Aug. 31, 2015—Zhoubing Xu, Ryan P. Burke, Christopher P. Lee, Rebeccah B. Baucom, Benjamin K. Poulose, Richard G. Abramson, Bennett A. Landman. “Efficient Multi-Atlas Abdominal Segmentation on Clinically Acquired CT with SIMPLE Context Learning.” Medical Image Analysis. In press May 2015. † Full Text: http://www.medicalimageanalysisjournal.com/article/S1361-8415(15)00076-6/fulltext Abstract Abdominal segmentation on clinically acquired computed tomography (CT) has been a...
Integrating histology and MRI in the first digital brain atlas of the common squirrel monkey, Saimiri sciureus
Feb. 12, 2015—Peizhen Sun, Prasanna Parvathaneni, Yurui Gao, Kurt G. Schilling, Vaibhav A. Janve, Adam W. Anderson, Bennett A. Landman. “Integrating histology and MRI in the first digital brain atlas of the common squirrel monkey, Saimiri sciureus.” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2015. † Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4405811/ Abstract This effort is...
Efficient Abdominal Segmentation on Clinically Acquired CT with SIMPLE Context Learning
Feb. 12, 2015—Zhoubing Xu, Ryan P. Burke, Christopher P. Lee, Rebeccah B. Baucom, Benjamin K. Poulose, Richard G. Abramson, Bennett A. Landman. “Efficient Abdominal Segmentation on Clinically Acquired CT with SIMPLE Context Learning.” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2015. † Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4405802/ Abstract Abdominal segmentation on clinically acquired computed tomography...