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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...

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Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service

Nov. 15, 2016—Shunxing Bao, Andrew Plassard, Bennett Landman and Aniruddha Gokhale. “Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service.”  IEEE International Conference on Cloud Engineering (IC2E), Vancouver, Canada, April 2017. Full text: NIHMSID Abstract Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval....

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Convergent individual differences in visual cortices, but not the amygdala across standard amygdalar fMRI probe tasks

Nov. 14, 2016—Victoria Villalta-Gil, Kendra E Hinton, Bennett A Landman, Benjamin C Yvernault, Scott F Perkins, Allison S Katsantonis, Courtney L Sellani, Benjamin B Lahey, David H Zald. “Convergent individual differences in visual cortices, but not the amygdala across standard amygdalar fMRI probe tasks.” NeuroImage. In Press November 2016 Open Data Resource: https://www.nitrc.org/projects/amygdalamapping Full text: NIHMSID Abstract...

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Simultaneous total intracranial volume and posterior fossa volume estimation using multi‐atlas label fusion

Oct. 31, 2016—Yuankai Huo, Andrew J. Asman, Andrew J. Plassard, Bennett A. Landman. “Simultaneous total intracranial volume and posterior fossa volume estimation using multi‐atlas label fusion.” Human Brain Mapping. In Press October 2016 Full text: https://www.ncbi.nlm.nih.gov/pubmed/27726243 Abstract Total intracranial volume (TICV) is an essential covariate in brain volumetric analyses. The prevalent brain imaging software packages provide automatic TICV estimates. FreeSurfer and FSL estimate TICV using a scaling factor while SPM12 accumulates probabilities of...

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Mapping Lifetime Brain Volumetry with Covariate-Adjusted Restricted Cubic Spline Regression from Cross-sectional Multi-site MRI

Oct. 30, 2016—Yuankai Huo, Katherine Aboud, Hakmook Kang, Laurie E. Cutting, Bennett A. Landman. “Mapping Lifetime Brain Volumetry with Covariate-Adjusted Restricted Cubic Spline Regression from Cross-sectional Multi-site MRI”. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Athens, Greece, October 2016. Oral Presentation. Full text: NIHMSID 826509 Abstract Understanding brain volumetry is essential to understand neurodevelopment...

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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

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SIMPLE Is a Good Idea (and Better with Context Learning)

Sep. 30, 2014—Zhoubing Xu, Andrew J. Asman, Peter L. Shanahan, Richard G. Abramson, Bennett A. Landman. “SIMPLE Is a Good Idea (and Better with Context Learning)”, In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Boston, MA, September 2014. Full text: PubMed Abstract Selective and iterative method for performance level estimation (SIMPLE) is a multi-atlas segmentation technique that integrates...

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Robust GM/WM Segmentation of the Spinal Cord with Iterative Non-Local Statistical Fusion

Oct. 30, 2013—Andrew J. Asman, Seth A. Smith, Daniel Reich, and Bennett A. Landman. “Robust GM/WM Segmentation of the Spinal Cord with Iterative Non-Local Statistical Fusion”, In Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). 2013 Nagoya, Japan Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3918679/ Abstract New magnetic resonance imaging (MRI) sequences are enabling clinical study of...

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Quantitative Evaluation of Statistical Inference in Resting State Functional MRI

Sep. 30, 2012—Xue Yang and Bennett A. Landman. “Quantitative Evaluation of Statistical Inference in Resting State Functional MRI”, In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Nice, France, September 2012 (32% acceptance rate) Full text: https://www.ncbi.nlm.nih.gov/pubmed/23286055 Abstract Modern statistical inference techniques may be able to improve the sensitivity and specificity of resting state functional...

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Collaborative Labeling of Malignant Glioma

May. 4, 2012—Zhoubing Xu, Andrew J. Asman, Eesha Singh, Lola Chambless, Reid Thompson, and Bennett A. Landman, “Collaborative Labeling of Malignant Glioma”, In Proceedings of the 2012 International Symposium on Biomedical Imaging (ISBI). Barcelona, Spain Full text: http://ieeexplore.ieee.org/abstract/document/6235763/ Abstract Malignant gliomas represent an aggressive class of central nervous system neoplasms which are often treated by maximal surgical resection....

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