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‘segmentation’

One the Fallacy of Quantitative Segmentation for T1-Weighted MRI.

Feb. 15, 2016—Andrew J. Plassard, Robert L. Harrigan, Allen T. Newton, Swati D. Rane, Srivatsan Pallavaram, Pierre F. D’Haese, Benoit M. Dawant, Daniel O. Claassen, Bennett A. Landman. “One the Fallacy of Quantitative Segmentation for T1-Weighted MRI.” 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/PMC4845960/ Abstract T1-weighted...

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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...

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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...

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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...

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Robust Optic Nerve Segmentation on Clinically Acquired CT

Dec. 31, 2014—Robert Harrigan, Swetasudha Panda, Andrew J. Asman, Michael P. DeLisi, Benjamin C. W. Yvernault, Seth A. Smith, Robert L. Galloway, Louise A. Mawn, Bennett A. Landman “Robust Optic Nerve Segmentation on Clinically Acquired CT.” Journal of Medical Imaging. 1(3), 034006 (Dec 17, 2014). † PMC3903299 Full Text: https://www.ncbi.nlm.nih.gov/pubmed/26158064 Abstract The optic nerve (ON) plays a...

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Non-Local Statistical Label Fusion for Multi-Atlas Segmentation.

Feb. 17, 2013—Andrew J. Asman and Bennett A. Landman. “Non-Local Statistical Label Fusion for Multi-Atlas Segmentation.” Medical Image Analysis (MEDIA). 2013. 17(2):194-208. PMC23265798 † Full Text: https://www.ncbi.nlm.nih.gov/pubmed/23265798 Abstract: Multi-atlas segmentation provides a general purpose, fully-automated approach for transferring spatial information from an existing dataset (“atlases”) to a previously unseen context (“target”) through image registration. The method to...

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Automatic Segmentation of Abdominal Wall in Ventral Hernia CT: A Pilot Study

Feb. 1, 2013—Zhoubing Xu, Wade M. Allen, Benjamin K. Poulose, Bennett A. Landman. “Automatic Segmentation of Abdominal Wall in Ventral Hernia CT: A Pilot Study.” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2013† Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877250/?report=classic   Abstract The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of...

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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...

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Foibles, Follies, and Fusion: Web-Based Collaboration for Medical Image Labeling

Jan. 31, 2012—Bennett A Landman, Andrew J Asman, Andrew G Scoggins, John A Bogovic, Joshua A Stein; Jerry L Prince, “Foibles, Follies, and Fusion: Web-Based Collaboration for Medical Image Labeling”, NeuroImage. 2012 Jan 2;59(1):530-9. PMC3195954 † Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3195954/ Abstract Labels that identify specific anatomical and functional structures within medical images are essential to the characterization of...

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Statistical Fusion of Surface Labels provided by Multiple Raters

Mar. 1, 2010—Bogovic, B. A. Landman, P.-L. Bazin, and J. L. Prince. “Statistical Fusion of Surface Labels provided by Multiple Raters, Over-complete, and Ancillary Data”, In Proceedings of the SPIE Medical Imaging Conference. San Diego, CA, February 2010 PMC2997739 Full Text: https://www.ncbi.nlm.nih.gov/pubmed/?term=Statistical+Fusion+of+Surface+Labels+provided+by+Multiple+Raters Abstract Studies of the size and morphology of anatomical structures rely on accurate and reproducible delineation...

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