Neuroimaging Category
Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging.
Apr. 15, 2013—Carolyn B. Lauzon, Andrew J. Asman, Michael L. Esparza, Scott S. Burns, Qiuyun Fan, Yurui Gao, Adam W. Anderson, Nicole Davis, Laurie E. Cutting, Bennett A. Landman. “Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging.” PLoS ONE. 2013 Apr 30;8(4) PMC23637895 † Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3640065/ Abstract Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural...
Assessment of Bias in MRI Diffusion Tensor Imaging Parameters Using SIMEX
Mar. 2, 2013—Carolyn B. Lauzon, Ciprian Crainiceanu, Brian C. Caffo, Bennett A. Landman, “Assessment of Bias in MRI Diffusion Tensor Imaging Parameters Using SIMEX”, Magnetic Resonance in Medicine. 2013 Mar 1;69(3):891-902. PMC22611000 † Full Text: https://www.ncbi.nlm.nih.gov/pubmed/22611000 Abstract: Diffusion tensor imaging enables in vivo investigation of tissue cytoarchitecture through parameter contrasts sensitive to water diffusion barriers at the...
Correcting Power and p-Value Calculations for Bias in Diffusion Tensor Imaging.
Mar. 2, 2013—Carolyn B. Lauzon and Bennett A. Landman, “Correcting Power and p-Value Calculations for Bias in Diffusion Tensor Imaging.” Magnetic Resonance Imaging. 2013 Mar 2. pii: S0730-725X(13) PMC23465764 † Full Text: https://www.ncbi.nlm.nih.gov/pubmed/?term=Correcting+Power+and+p-Value+Calculations+for+Bias+in+Diffusion+Tensor+Imaging. Abstract: Diffusion tensor imaging (DTI) provides quantitative parametric maps sensitive to tissue microarchitecture (e.g., fractional anisotropy, FA). These maps are estimated through computational processes and...
Integration of XNAT/PACS, DICOM, and Research Software for Automated Multi-modal Image Analysis
Feb. 1, 2013—Yurui Gao, Scott S. Burns, Carolyn B. Lauzon, Andrew Fong, David A. Twillie, Michael Wirt, Marc A. Zola, Bret W. Logan, Adam W. Anderson, Bennett A. Landman. “Integration of XNAT/PACS, DICOM, and Research Software for Automated Multi-modal Image Analysis.” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2013. Oral Presentation. † Full...
System for Integrated Neuroimaging Analysis and Processing of Structure.
Jan. 11, 2013—Bennett A. Landman, John A. Bogovic, Aaron Carass, Min Chen, Snehashis Roy, Navid Shiee, Zhen Yang, Bhaskar Kishore, Dzung Pham, Pierre-Louis Bazin, Susan M. Resnick, and Jerry L. Prince. “System for Integrated Neuroimaging Analysis and Processing of Structure.” Neuroinformatics. 2013 Jan;11(1):91-10 PMC22932976 † Full Text: https://www.ncbi.nlm.nih.gov/pubmed/22932976 Abstract: Mapping brain structure in relation to neurological development,...
Out-of-Atlas Labeling: A Multi-Atlas Approach to Cancer Segmentation
Dec. 31, 2012—Andrew J. Asman and Bennett A. Landman, “Out-of-Atlas Labeling: A Multi-Atlas Approach to Cancer Segmentation”, In Proceedings of the 2012 International Symposium on Biomedical Imaging (ISBI). Barcelona, Spain† Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3892947/ Abstract Conventional automated segmentation techniques for magnetic resonance imaging (MRI) fail to perform in a robust and consistent manner when brain anatomy differs...
Segmentation of Malignant Gliomas through Remote Collaboration and Statistical Fusion.
Oct. 31, 2012—Zhoubing Xu, Andrew J. Asman, Eesha Singh, Lola Chambless, Reid Thompson, Bennett A. Landman. “Segmentation of Malignant Gliomas through Remote Collaboration and Statistical Fusion.” Medical Physics. 2012 Oct;39(10):5981-9 PMC3461053 † Full Text: https://www.ncbi.nlm.nih.gov/pubmed/?term=Segmentation+of+Malignant+Gliomas+through+Remote+Collaboration+and+Statistical+Fusion. Abstract: PURPOSE: Malignant gliomas represent an aggressive class of central nervous system neoplasms. Correlation of interventional outcomes with tumor morphometry data necessitates 3D...
Biological Parametric Mapping Accounting for Random Regressors with Regression Calibration and Model II Regression
Sep. 1, 2012—Xue Yang, Carolyn B. Lauzon, Ciprian Crainiceanu, Brian Caffo, Susan M. Resnick, Bennett A. Landman. “Biological Parametric Mapping Accounting for Random Regressors with Regression Calibration and Model II Regression.” NeuroImage. 2012 Sep;62(3):1761-8. PMC22609453 Full text: https://www.ncbi.nlm.nih.gov/pubmed/22609453 Abstract Massively univariate regression and inference in the form of statistical parametric mapping have transformed the way in which multi-dimensional...
Formulating Spatially Varying Performance in the Statistical Fusion Framework
Jul. 31, 2012—Andrew J. Asman and Bennett A. Landman, “Formulating Spatially Varying Performance in the Statistical Fusion Framework”, IEEE Transactions on Medical Imaging. 2012 Jun;31(6):1326-36. PMC3368083 † Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368083/ Abstract To date, label fusion methods have primarily relied either on global (e.g. STAPLE, globally weighted vote) or voxelwise (e.g. locally weighted vote) performance models. Optimality of...
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....