Skip to main content

Author

Learning 3D White Matter Microstructure from 2D Histology

Apr. 1, 2019—Histological analysis is typically the gold standard for validating measures of tissue microstructure derived from magnetic resonance imaging (MRI) contrasts. However, most histological investigations are inherently 2-dimensional (2D), due to increased field-of-view, higher in-plane resolutions, ease of acquisition, decreased costs, and a large number of available contrasts compared to 3-dimensional (3D) analysis. Because of this,...

Read more


Inter-Scanner Harmonization of High Angular Resolution DW-MRI using Null Space Deep Learning

Sep. 10, 2018—Vishwesh Nath, Prasanna Parvathaneni, Colin B. Hansen, Allison E. Hainline, Camilo Bermudez, Samuel Remedios, Justin A. Blaber, Kurt G. Schilling, Ilwoo Lyu, Vaibhav Janve, Yurui Gao, Iwona Stepniewska, Baxter P. Rogers, Allen T. Newton, L. Taylor Davis, Jeff Luci, Adam W. Anderson and Bennett A. Landman (Accepted at Computation Diffusion MRI Workshop at MICCAI 2018) Abstract....

Read more


SHARD: Spherical Harmonic-based Robust Outlier Detection for HARDI Methods

Dec. 19, 2017—Citation: ” SHARD: Spherical Harmonic-based Robust Outlier Detection for HARDI Methods”. Vishwesh Nath, Ilwoo Lyu, Kurt G. Schilling, Allison E. Hainline, Prasanna Parvathaneni,  Justin A. Blaber, Ilwoo Lyu, Adam W. Anderson, Hakmook Kang, Allen T. Newton, Baxter P. Rogers, Bennett A. Landman   In SPIE Medical Imaging, International Society for Optics and Photonics, 2018 (Accepted) Abstract:  High Angular...

Read more


Evaluation of Body-Wise and Organ-Wise Registrations for Abdominal Organs

Apr. 15, 2016—Zhoubing Xu, Sahil A. Panjwani, Christopher P. Lee, Ryan P. Burke, Rebeccah B. Baucom, Benjamin K. Poulose, Richard G. Abramson, Bennett A. Landman, “Evaluation of Body-Wise and Organ-Wise Registrations for Abdominal Organs”, 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/PMC4845963/   Abstract Identifying cross-sectional and...

Read more


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...

Read more


A Bayesian Framework for Early Risk Prediction in Traumatic Brain Injury

Feb. 15, 2016—Shikha Chaganti, Andrew J. Plassard, Laura Wilson, Miya A. Smith, Mayur B. Patel, Bennett A. Landman. A Bayesian Framework for Early Risk Prediction in Traumatic Brain Injury. In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2016. Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4845965/   Abstract Early detection of risk is critical in determining the course...

Read more


Groupwise Multi-Atlas Segmentation of the Spinal Cord’s Internal Structure.

Apr. 15, 2014—Andrew J. Asman, Frederick W. Bryan, Seth A. Smith, Daniel S. Reich, Bennett A. Landman. “Groupwise Multi-Atlas Segmentation of the Spinal Cord’s Internal Structure.” Medical Image Analysis (MedIA). 2014 Feb 5;18(3):460-471. PMC24556080† Full Text:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009677/   Abstract The spinal cord is an essential and vulnerable component of the central nervous system. Differentiating and localizing the spinal...

Read more


Self-Assessed Performance Improves Statistical Fusion of Image Labels.

Feb. 15, 2014—Frederick W. Bryan, Zhoubing Xu, Andrew J. Asman, Wade M. Allen, Daniel S. Reich, and Bennett A. Landman. “Self-Assessed Performance Improves Statistical Fusion of Image Labels.” Medical Physics. 2014 Mar;41(3):031903. PMC24593721† Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978333/   Abstract Purpose: Expert manual labeling is the gold standard for image segmentation, but this process is difficult, time-consuming, and prone...

Read more


Texture Analysis Improves Level Set Segmentation of the Anterior Abdominal Wall.

Dec. 15, 2013—Zhoubing Xu, Wade M. Allen, Rebeccah B. Baucom, Benjamin K. Poulose, Bennett A. Landman. “Texture Analysis Improves Level Set Segmentation of the Anterior Abdominal Wall.” Medical Physics. 2013 Dec;40(12):121901. † PMC3838426 Full Text: https://www.ncbi.nlm.nih.gov/pubmed/24320512 Abstract PURPOSE: The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is...

Read more


Out-of-Atlas Likelihood Estimation using Multi-Atlas Segmentation.

Apr. 15, 2013—Andrew J. Asman, Lola Chambless, Reid Thompson, and Bennett A. Landman. “Out-of-Atlas Likelihood Estimation using Multi-Atlas Segmentation.” Medical Physics. 2013 Apr;40(4) PMC23556928 † Full-Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3625241/   Abstract Purpose: Multi-atlas segmentation has been shown to be highly robust and accurate across an extraordinary range of potential applications. However, it is limited to the segmentation of structures...

Read more