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Neuroimaging Category

Anatomical context improves deep learning on the brain age estimation task

Jul. 12, 2019—Bermudez, C., Plassard, A. J., Chaganti, S., Huo, Y., Aboud, K. E., Cutting, L. E., … & Landman, B. A. (2019). Anatomical context improves deep learning on the brain age estimation task. Magnetic Resonance Imaging. Full Text: https://www.ncbi.nlm.nih.gov/pubmed/31247249 Abstract Deep learning has shown remarkable improvements in the analysis of medical images without the need for...

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Improved gray matter surface based spatial statistics in neuroimaging studies

May. 21, 2019—Prasanna Parvathaneni; Ilwoo Lyu; Yuankai Huo; Baxter P. Rogers; Kurt G. Schilling; Vishwesh Nath; Justin A Blaber; Allison E Hainline; Adam W Anderson; Neil D. Woodward; Bennett A Landman. “Improved gray matter surface based spatial statistics in neuroimaging studies.” In MRI – Accepted. Abstract Neuroimaging often involves acquiring high-resolution anatomical images along with other low-resolution image modalities,...

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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,...

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A Web-based Combined MRI-Histology Digital Atlas of the Squirrel Monkey Brain.

Dec. 15, 2018—Kurt G. Schilling, Yurui Gao, Vaibhav Janve, Matthew Christian, Iwona Stepniewska, Bennett A. Landman, Adam W. Anderson. “A Web-based Combined MRI-Histology Digital Atlas of the Squirrel Monkey Brain.” Neuroinformatics (2018) 1-15. doi:10.1007/s12021-018-9391-z. Full text: https://www.ncbi.nlm.nih.gov/pubmed/?term=A+Web-based+Combined+MRI-Histology+Digital+Atlas Abstract  The squirrel monkey (Saimiri sciureus) is a commonly-used surrogate for humans in biomedical research. In the neuroimaging community, MRI...

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Challenges in diffusion MRI tractography – Lessons learned from international benchmark competitions

Dec. 15, 2018—Kurt G Schilling, Alessandro Daducci, Klaus Maier-Hein, Cyril Poupon, Jean-Christophe Houde, Vishwesh Nath, Adam W Anderson, Bennett A Landman, Maxime Descoteaux. “Challenges in Diffusion MRI Tractography – Lessons Learned from International Benchmark Competitions”. Magnetic Resonance Imaging. 2018. doi: 10.1016/j.mri.2018.11.014 Full text: NIHMSID https://www.sciencedirect.com/science/article/pii/S0730725X18305162#f0005 Abstract Diffusion MRI (dMRI) fiber tractography has become a pillar of the neuroimaging...

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Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps

Dec. 10, 2018—Bermudez, C., Rodriguez, W., Huo, Y., Hainline, A. E., Li, R., Shults, R., … & Landman, B. A. (2018). Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps. arXiv preprint arXiv:1811.10415. Full Text: https://arxiv.org/abs/1811.10415 Abstract Deep brain stimulation (DBS) has the potential to improve the quality of life of people with a...

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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....

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Constructing Statistically Unbiased Cortical Surface Templates Using Feature Space Covariance

Dec. 19, 2017—Citation: ” Constructing statistically unbiased cortical surface templates using feature-space covariance”. Prasanna Parvathaneni, Ilwoo Lyu, Justin A. Blaber, Yuankai Huo, Allison E. Hainline, Neil D. Woodward, Hakmook Kang, Bennett A. Landman   In SPIE Medical Imaging, International Society for Optics and Photonics, 2018 (Accepted). Abstract The choice of surface template plays an important role in cross-sectional subject analyses...

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4D Multi-atlas Label Fusion using Longitudinal Images

Aug. 29, 2017—Yuankai Huo, Susan M. Resnick and Bennett A. Landman. “4D Multi-atlas Label Fusion using Longitudinal Images”. MICCAI Patch-MI Workshop, 2017. Full text: https://drive.google.com/open?id=0Bzzeqiij2Zara1ZlQXJiclM2UEE Abstract Longitudinal reproducibility is an essential concern in automated medical image segmentation, yet has proven to be an elusive objective as manual brain structure tracings have shown more than 10% variability. To improve reproducibility, longitudinal...

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Gray Matter Surface based Spatial Statistics (GS-BSS) in Diffusion Microstructure

Aug. 28, 2017—Citation: Gray Matter Surface based Spatial Statistics (GS-BSS) in Diffusion Microstructure. Authors: Prasanna Parvatheni, Baxter P. Rogers, Yuankai Huo, Kurt G. Schilling, Allison E. Hainline, Adam W. Anderson, Neil D. Woodward, Bennett A. Landman. International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer. (2017). Accepted.  Abstract Tract-based spatial statistics (TBSS) has proven to be...

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