Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challenge.

Autor: Nath V; Computer Science, Vanderbilt University, Nashville, Tennessee, USA., Schilling KG; Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA., Parvathaneni P; Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA., Huo Y; Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA., Blaber JA; Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA., Hainline AE; Biostatistics, Vanderbilt University, Nashville, Tennessee, USA., Barakovic M; Signal Processing Lab (LTS5), EPFL, Switzerland., Romascano D; Signal Processing Lab (LTS5), EPFL, Switzerland., Rafael-Patino J; Signal Processing Lab (LTS5), EPFL, Switzerland., Frigo M; Signal Processing Lab (LTS5), EPFL, Switzerland., Girard G; Signal Processing Lab (LTS5), EPFL, Switzerland., Thiran JP; Signal Processing Lab (LTS5), EPFL, Switzerland., Daducci A; Computer Science Department, University of Verona, Italy., Rowe M; Mint Labs Inc., Boston, Massachusetts, USA., Rodrigues P; Mint Labs Inc., Boston, Massachusetts, USA., Prčkovska V; Mint Labs Inc., Boston, Massachusetts, USA., Aydogan DB; Keck School of Medicine, University of Southern California (NICR), Los Angeles, California, USA., Sun W; Keck School of Medicine, University of Southern California (NICR), Los Angeles, California, USA., Shi Y; Keck School of Medicine, University of Southern California (NICR), Los Angeles, California, USA., Parker WA; Center for Biomedical Image Computing and Analytics, Dept. of Radiology, Perelman School of Medicine, University of Pennsylvania (UPENN), Philadelphia, Pennsylvania, USA., Ould Ismail AA; Center for Biomedical Image Computing and Analytics, Dept. of Radiology, Perelman School of Medicine, University of Pennsylvania (UPENN), Philadelphia, Pennsylvania, USA., Verma R; Center for Biomedical Image Computing and Analytics, Dept. of Radiology, Perelman School of Medicine, University of Pennsylvania (UPENN), Philadelphia, Pennsylvania, USA., Cabeen RP; Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA., Toga AW; Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA., Newton AT; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Wasserthal J; Medical Image Computing Group, German Cancer Research Center (DKFZ), Heidelberg, Germany., Neher P; Medical Image Computing Group, German Cancer Research Center (DKFZ), Heidelberg, Germany., Maier-Hein K; Medical Image Computing Group, German Cancer Research Center (DKFZ), Heidelberg, Germany., Savini G; Department of Physics, University of Milan, Milan, Italy., Palesi F; Brain Connectivity Center, C. Mondino National Neurological Institute (EFG), Pavia, Italy., Kaden E; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK., Wu Y; Institution of Information Processing and Automation, Zhejiang University of Technology (ZUT), Hangzhou, China., He J; Institution of Information Processing and Automation, Zhejiang University of Technology (ZUT), Hangzhou, China., Feng Y; Institution of Information Processing and Automation, Zhejiang University of Technology (ZUT), Hangzhou, China., Paquette M; Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada., Rheault F; Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada., Sidhu J; Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada., Lebel C; Department of Radiology, University of Calgary, Canada., Leemans A; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands., Descoteaux M; Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada., Dyrby TB; Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital, Hvidovre, Denmark., Kang H; Biostatistics, Vanderbilt University, Nashville, Tennessee, USA., Landman BA; Computer Science, Vanderbilt University, Nashville, Tennessee, USA.; Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.; Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA.; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

Publikováno v: Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2020 Jan; Vol. 51 (1), pp. 234-249. Date of Electronic Publication: 2019 Jun 09.

Improved gray matter surface based spatial statistics in neuroimaging studies.

Autor: Parvathaneni P; Electrical Engineering, Vanderbilt University, Nashville, TN, USA. Electronic address: Prasanna.Parvathaneni@Vanderbilt.edu., Lyu I; Computer Science, Vanderbilt University, Nashville, TN, USA., Huo Y; Electrical Engineering, Vanderbilt University, Nashville, TN, USA., Rogers BP; Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA., Schilling KG; Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA., Nath V; Computer Science, Vanderbilt University, Nashville, TN, USA., Blaber JA; Electrical Engineering, Vanderbilt University, Nashville, TN, USA., Hainline AE; Biostatistics, Vanderbilt University, Nashville, TN, USA., Anderson AW; Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA., Woodward ND; Department of Psychiatry and Behavioral Sciences, Vanderbilt University, Nashville, TN, USA., Landman BA; Electrical Engineering, Vanderbilt University, Nashville, TN, USA; Computer Science, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Psychiatry and Behavioral Sciences, Vanderbilt University, Nashville, TN, USA.

Publikováno v: Magnetic resonance imaging [Magn Reson Imaging] 2019 Sep; Vol. 61, pp. 285-295. Date of Electronic Publication: 2019 May 22.

Characterization and correlation of signal drift in diffusion weighted MRI.

Autor: Hansen CB; Computer Science, Vanderbilt University, Nashville, TN, USA. Electronic address: colin.b.hansen@vanderbilt.edu., Nath V; Computer Science, Vanderbilt University, Nashville, TN, USA., Hainline AE; Biostatistics, Vanderbilt University, Nashville, TN, USA., Schilling KG; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA., Parvathaneni P; Electrical Engineering, Vanderbilt University, Nashville, TN, USA., Bayrak RG; Computer Science, Vanderbilt University, Nashville, TN, USA., Blaber JA; Electrical Engineering, Vanderbilt University, Nashville, TN, USA., Irfanoglu O; National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD, USA., Pierpaoli C; National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD, USA., Anderson AW; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA., Rogers BP; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA., Landman BA; Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Electrical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.

Publikováno v: Magnetic resonance imaging [Magn Reson Imaging] 2019 Apr; Vol. 57, pp. 133-142. Date of Electronic Publication: 2018 Nov 22.

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

Autor: Bermudez C; Department of Biomedical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235., Rodriguez W; Department of Electrical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235., Huo Y; Department of Electrical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235., Hainline AE; Department of Biostatistics, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235., Li R; Department of Electrical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235., Shults R; Department of Electrical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235., D'Haese PD; Department of Electrical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235.; Department of Neurosurgery, Vanderbilt University Medical Center, 2201 West End Ave, Nashville, TN, USA 37235., Konrad PE; Department of Neurosurgery, Vanderbilt University Medical Center, 2201 West End Ave, Nashville, TN, USA 37235., Dawant BM; Department of Biomedical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235.; Department of Electrical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235., Landman BA; Department of Biomedical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235.; Department of Electrical Engineering, Vanderbilt University, 2201 West End Ave, Nashville, TN, USA 37235.

Publikováno v: Proceedings of SPIE--the International Society for Optical Engineering [Proc SPIE Int Soc Opt Eng] 2019 Mar; Vol. 10949.

Empirical single sample quantification of bias and variance in Q-ball imaging.

Autor: Hainline AE; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Nath V; Department of Computer Science, Vanderbilt University, Nashville, Tennessee, USA., Parvathaneni P; Department of Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA., Blaber JA; Department of Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA., Schilling KG; Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA., Anderson AW; Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Kang H; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Center for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Landman BA; Department of Computer Science, Vanderbilt University, Nashville, Tennessee, USA.; Department of Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA.; Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Center for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

Publikováno v: Magnetic resonance in medicine [Magn Reson Med] 2018 Oct; Vol. 80 (4), pp. 1666-1675. Date of Electronic Publication: 2018 Feb 06.