Stephen C. Strother

发表

Nonlinear versus Linear Models in Functional Neuroimaging: Learning Curves and Generalization Crossover

Lars Kai Hansen, Olaf B. Paulson, Niels J. S. Mørch, 1997, IPMI.

The Center for Integrated Molecular Brain Imaging (Cimbi) database

Hartwig R. Siebner, Lars Kai Hansen, Olaf B. Paulson, 2016, NeuroImage.

Pattern classification of fMRI data: Applications for analysis of spatially distributed cortical networks

Stephen C. Strother, Grigori Yourganov, Tanya Schmah, 2014, NeuroImage.

Graynet: Single-subject Morphometric Networks for Neuroscience Connectivity Applications

Stephen C. Strother, Pradeep Reddy Raamana, 2018, J. Open Source Softw..

Model sparsity and brain pattern interpretation of classification models in neuroimaging

Lars Kai Hansen, Stephen C. Strother, Kristoffer Hougaard Madsen, 2012, Pattern Recognit..

Evaluating subject specific preprocessing choices in multisubject fMRI data sets using data-driven performance metrics

Gary F. Egan, Stephen C. Strother, Marnie E. Shaw, 2003, NeuroImage.

Visualization of Nonlinear Classification Models in Neuroimaging - Signed Sensitivity Maps

Lars Kai Hansen, Stephen C. Strother, Kristoffer Hougaard Madsen, 2012, BIOSIGNALS.

Effect of Spatial Alignment Transformations in PCA and ICA of Functional Neuroimages

Yongyi Yang, Lars Kai Hansen, Stephen C. Strother, 2007, IEEE Transactions on Medical Imaging.

Machine Learning in Medical Imaging

Yongyi Yang, Stephen C. Strother, Jovan G. Brankov, 2010, IEEE Signal Processing Magazine.

Evaluating and optimizingfmri processing pipelines with the npairs approach for decision support in fmri applications

Jing Zhang, Stephen C. Strother, Laël C. Gatewood, 2005 .

Support vector machines for temporal classification of block design fMRI data

Stephen C. Strother, Xiaoping Hu, Vladimir Cherkassky, 2005, NeuroImage.

The Quantitative Evaluation of Functional Neuroimaging Experiments: The NPAIRS Data Analysis Framework

Lars Kai Hansen, Jon Anderson, Stephen C. Strother, 2000, NeuroImage.

Mapping cerebral blood flow during speech production in hereditary ataxia

Stephen C. Strother, David A. Rottenberg, John J. Sidtis, 2006, NeuroImage.

Penalized Discriminant Analysis of [15O]-water PET Brain Images with Prediction Error Selection of Smoothness and Regularization

Stephen C. Strother, Rafal Kustra, S. Strother, 2001, IEEE Trans. Medical Imaging.

Data-driven evaluation and optimization of acquisition strategies for ultra-high-field functional MRI at 7 Tesla

Stephen C. Strother, Robert L. Barry, John C. Gore, 2010, 2010 Biomedical Sciences and Engineering Conference.

An ICA algorithm for analyzing multiple data sets

Lars Kai Hansen, Stephen C. Strother, Miles N. Wernick, 2002, Proceedings. International Conference on Image Processing.

A novel iterative reconstruction algorithm for emission computed tomography

Jeih-San Liow, Stephen C. Strother, Xiao-Liang Xu, 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Python Class (Data Structure) To Ease And Improve Machine Learning Workflow

Stephen C. Strother, Pradeep Reddy Raamana, 2017 .

A signal-detection approach for analysis of functional neuroimages

Yongyi Yang, Stephen C. Strother, Miles N. Wernick, 2001, 2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310).

The association between cerebrovascular reactivity and resting-state fMRI functional connectivity in healthy adults: The influence of basal carbon dioxide

Stephen C. Strother, J. Jean Chen, Ali-Mohammad Golestani, 2016, NeuroImage.

Optimizing fMRI preprocessing pipelines for block-design tasks as a function of age

Stephen C. Strother, Nathan William Churchill, Pradeep Reddy Raamana, 2017, NeuroImage.

Introduction to the Issue on Advanced Signal Processing for Brain Networks

Dimitri Van De Ville, Stephen C. Strother, Jonas Richiardi, 2016, IEEE J. Sel. Top. Signal Process..

Optimization of preprocessing strategies in Positron Emission Tomography (PET) neuroimaging: A [11C]DASB PET study

Stephen C. Strother, Claus Svarer, Gitte Moos Knudsen, 2019, NeuroImage.

Preprocessing, Prediction and Significance: Framework and Application to Brain Imaging

Stephen C. Strother, Claus Svarer, Vibe G. Frokjaer, 2019, MICCAI.

Data-driven optimization and evaluation of 2D EPI and 3D PRESTO for BOLD fMRI at 7 Tesla: I. Focal coverage

Stephen C. Strother, Robert L. Barry, John C. Gore, 2011, NeuroImage.

PHYCAA: Data-driven measurement and removal of physiological noise in BOLD fMRI

Stephen C. Strother, Grigori Yourganov, Nathan William Churchill, 2012, NeuroImage.

BIDS Apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods

M. Mallar Chakravarty, Anisha Keshavan, Russell A. Poldrack, 2016 .

The CAMH Neuroinformatics Platform: A Hospital-Focused Brain-CODE Implementation

Stephen C. Strother, Fan Dong, Stephen R. Arnott, 2018, Front. Neuroinform..

Comparing reconstruction algorithms using a multi-variate analysis

Jeih-San Liow, Stephen C. Strother, Jon R. Anderson, 1999, 1999 IEEE Nuclear Science Symposium. Conference Record. 1999 Nuclear Science Symposium and Medical Imaging Conference (Cat. No.99CH37019).

Generative versus discriminative training of RBMs for classification of fMRI images

Geoffrey E. Hinton, Stephen C. Strother, Richard S. Zemel, 2008, NIPS.

Correction: An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

Stephen C. Strother, Fan Dong, Robyn Spring, 2015, PloS one.

Enhancing reproducibility of fMRI statistical maps using generalized canonical correlation analysis in NPAIRS framework

Gholam-Ali Hossein-Zadeh, Stephen C. Strother, Hamid Soltanian-Zadeh, 2012, NeuroImage.

Porting a neuro-imaging application to a CPU-GPU cluster

Stephen C. Strother, Cristiana Amza, Sahel Sharify, 2014, 2014 International Conference on High Performance Computing & Simulation (HPCS).

Reversible jump Markov chain Monte Carlo signal detection in functional neuroimaging analysis

Nikolas P. Galatsanos, Yongyi Yang, Stephen C. Strother, 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

PHYCAA+: An optimized, adaptive procedure for measuring and controlling physiological noise in BOLD fMRI

Stephen C. Strother, Nathan William Churchill, S. Strother, 2013, NeuroImage.

Comparing Classification Methods for Longitudinal fMRI Studies

Geoffrey E. Hinton, Stephen C. Strother, Richard S. Zemel, 2010, Neural Computation.

A developer’s commentary on fiswidgets

Stephen C. Strother, 2003, Neuroinformatics.

Visualization of neural networks using saliency maps

Lars Kai Hansen, Niels J. S. Mørch, Stephen C. Strother, 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

The Associative Memory Deficit in Aging Is Related to Reduced Selectivity of Brain Activity during Encoding

Stephen C. Strother, Cheryl L. Grady, Saman Sarraf, 2016, Journal of Cognitive Neuroscience.

Functional connectivity during Stroop task performance

Gary F. Egan, Stephen C. Strother, Marnie E. Shaw, 2005, NeuroImage.

A reversible jump Markov chain Monte Carlo algorithm for analysis of functional neuroimages

Nikolas P. Galatsanos, Yongyi Yang, Stephen C. Strother, 2002, Proceedings. International Conference on Image Processing.

Bayesian Kernel Methods for Analysis of Functional Neuroimages

Xu Chen, Nikolas P. Galatsanos, Yongyi Yang, 2007, IEEE Transactions on Medical Imaging.

SYSTEMATIC COMPARISON OF CORTICAL THICKNESS BASED NETWORKS

Stephen C. Strother, Pradeep Reddy Raamana, 2016, Alzheimer's & Dementia.

A Java-based fMRI Processing Pipeline Evaluation System for Assessment of Univariate General Linear Model and Multivariate Canonical Variate Analysis-based Pipelines

Jing Zhang, Stephen C. Strother, David A. Rottenberg, 2008, Neuroinformatics.

The NPAIRS Computational Statistics Framework for Data Analysis in Neuroimaging

Stephen C. Strother, Robyn Spring, Anita Oder, 2010, COMPSTAT.

Impact of inter-subject image registration on group analysis of fMRI data

Stephen C. Strother, Babak A. Ardekani, Yoshiharu Yonekura, 2004 .

Evaluation of spatio-temporal decomposition techniques for group analysis of fMRI resting state data sets

Stephen C. Strother, Cheryl L. Grady, Babak Afshin-Pour, 2014, NeuroImage.

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data

Stephen C. Strother, Fan Dong, Stephen R. Arnott, 2018, Front. Neuroinform..

Enhancing the Multivariate Signal of [15O] water PET Studies with a New Non-Linear Neuroanatomical Registration Algorithm

Lars Kai Hansen, Stephen C. Strother, Ian Law, 1999, IEEE Trans. Medical Imaging.

Dimensionality estimation for optimal detection of functional networks in BOLD fMRI data

Xu Chen, Stephen C. Strother, Steven L. Small, 2011, NeuroImage.

Chapter 73 - [ 15 O]Water PET More “Noise” Than Signal?

Lars Kai Hansen, Stephen C. Strother, David A. Rottenberg, 1996 .

VisualQC: rigorous yet easy quality control of neuroimaging and medical data

Stephen C. Strother, Pradeep Reddy Raamana, 2018 .

Novel histogram-weighted cortical thickness networks and a multi-scale analysis of predictive power in Alzheimer's disease

Stephen C. Strother, Pradeep Reddy Raamana, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

The suppression of scale-free fMRI brain dynamics across three different sources of effort: aging, task novelty and task difficulty

Stephen C. Strother, Marc G. Berman, Scott Peltier, 2016, Scientific Reports.

mrivis: Medical image visualization library for neuroscience in python

Stephen C. Strother, Pradeep Reddy Raamana, 2018, J. Open Source Softw..

A spatially robust ICA algorithm for multiple fMRI data sets

Lars Kai Hansen, Stephen C. Strother, Miles N. Wernick, 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

The structure of the serotonin system: A PET imaging study

Stephen C. Strother, Claus Svarer, Gitte Moos Knudsen, 2020, NeuroImage.

A symbolic environment for visualizing activated foci in functional neuroimaging datasets

Stephen C. Strother, David A. Rottenberg, Kelly Rehm, 1998, Medical Image Anal..

Group specific optimisation of fMRI processing steps for child and adult data

Stephen C. Strother, Rebecca M. Todd, Margot J. Taylor, 2010, NeuroImage.

Comparison of two convolution models for fMRI time series

Bruce R. Rosen, Lars Kai Hansen, Egill Rostrup, 1997 .

Standardized and easy predictive analysis: proposal, tools and infrastructure

Stephen C. Strother, Pradeep Reddy Raamana, 2018 .

Generalizable Singular Value Decomposition for Ill-posed Datasets

Lars Kai Hansen, Stephen C. Strother, Ulrik Kjems, 2000, NIPS.

An overview of the quality assurance and quality control of magnetic resonance imaging data for the Ontario Neurodegenerative Disease Research Initiative (ONDRI): pipeline development and neuroinformatics

Stephen C. Strother, Fan Dong, Stephen R. Arnott, 2020, bioRxiv.

Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA.

Stephen C. Strother, David A. Rottenberg, Jon R. Anderson, 2009, Magnetic resonance imaging.

Predictive relationship between functional activation pattern and kinematic parameters in a PET study of motor learning

Stephen C. Strother, David A. Rottenberg, John J. Sidtis, 1999 .

Spatiotemporal fMRI data processing using generalized canonical correlation analysis

Gholam-Ali Hossein-Zadeh, Hamid Soltanian-Zadeh, Stephen C. Strother, 2010, 2010 17th Iranian Conference of Biomedical Engineering (ICBME).

Impact of spatial scale and edge weight on predictive power of cortical thickness networks

Stephen C. Strother, Pradeep Reddy Raamana, S. Strother, 2017 .

Histogram-weighted Networks for Feature Extraction, Connectivity and Advanced Analysis in Neuroscience

Stephen C. Strother, Pradeep Reddy Raamana, 2017, J. Open Source Softw..

The Impact of Preprocessing Pipeline Choice in Univariate and Multivariate Analyses of PET Data

Stephen C. Strother, Claus Svarer, Gitte Moos Knudsen, 2018, 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Optimizing Preprocessing and Analysis Pipelines for Single-Subject fMRI: 2. Interactions with ICA, PCA, Task Contrast and Inter-Subject Heterogeneity

Stephen C. Strother, Grigori Yourganov, Fred Tam, 2012, PloS one.

A hierarchy of cognitive brain networks revealed by multivariate performance metrics

Stephen C. Strother, Cheryl L. Grady, Saman Sarraf, 2014, 2014 48th Asilomar Conference on Signals, Systems and Computers.

Python class defining a machine learning dataset ensuring key-based correspondence and maintaining integrity

Stephen C. Strother, Pradeep Reddy Raamana, 2017, J. Open Source Softw..

The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics

Essa Yacoub, Lars Kai Hansen, Stephen C. Strother, 2003, NeuroImage.

A Hybrid LDA+gCCA Model for fMRI Data Classification and Visualization

Stephen C. Strother, Seyed-Mohammad Shams, Babak Afshin-Pour, 2015, IEEE Transactions on Medical Imaging.

A computerized tablet with visual feedback of hand position for functional magnetic resonance imaging

Stephen C. Strother, Fred Tam, Simon J. Graham, 2015, Front. Hum. Neurosci..

Predicting Motor Tasks in fMRI Data with Support Vector Machines

Stephen C. Strother, Vladimir Cherkassky, Xiaoping Hu, 2003 .

An evaluation of methods for detecting brain activations from functional neuroimages

Stephen C. Strother, Miles N. Wernick, Ana S. Lukic, 2002, Artif. Intell. Medicine.

A mutual information‐based metric for evaluation of fMRI data‐processing approaches

Gholam-Ali Hossein-Zadeh, Stephen C. Strother, Hamid Soltanian-Zadeh, 2011, Human brain mapping.

Review of Preprocessing Steps for BOLD fMRI

Stephen C. Strother, S. Strother, 2006 .

Evaluation and comparison of GLM- and CVA-based fMRI processing pipelines with Java-based fMRI processing pipeline evaluation system

Stephen C. Strother, David A. Rottenberg, Jing Zhang, 2008, NeuroImage.

Consensus Inference in Neuroimaging

Lars Kai Hansen, Stephen C. Strother, Finn Årup Nielsen, 2001, NeuroImage.

Improved Segmentation of the Intracranial and Ventricular Volumes in Populations with Cerebrovascular Lesions and Atrophy Using 3D CNNs

Stephen C. Strother, Emmanuel E. Ntiri, Melissa F. Holmes, 2021, Neuroinformatics.

Magnetic Resonance Imaging Sequence Identification Using a Metadata Learning Approach

Stephen C. Strother, Stephen R. Arnott, Sean Symons, 2021, Frontiers in Neuroinformatics.

Abnormal Functional Connectivity in Posttraumatic Stress Disorder

Gary F. Egan, Stephen C. Strother, Marnie E. Shaw, 2002, NeuroImage.

Are Brain Functions Really Additive?

Stephen C. Strother, David A. Rottenberg, John J. Sidtis, 1996, NeuroImage.

Establishing Behavioral Correlates of Functional Imaging Signals

Stephen C. Strother, David A. Rottenberg, John J. Sidtis, 2001 .

How many Principal Components

Bruce R. Rosen, Lars Kai Hansen, Egill Rostrup, 1997 .

Effects of Changes in Experimental Design on PET Studies of Isometric Force

Stephen C. Strother, David A. Rottenberg, John J. Sidtis, 2001, NeuroImage.

Practical Tradeoffs Between Noise, Resolution And Quantitation, And Number Of Iterations For Maximum Likelihood Reconstructions

Jeih-San Liow, Stephen C. Strother, S. Strother, 1990, 1990 IEEE Nuclear Science Symposium Conference Record.

Generalization of the minimum covariance determinant algorithm for categorical and mixed data types

Stephen C. Strother, Hervé Abdi, Richard H. Swartz, 2018, bioRxiv.

Improved resolution via 3D iterative reconstruction for PET volume imaging

Jeih-San Liow, Stephen C. Strother, David A. Rottenberg, 1994, Proceedings of 1994 IEEE Nuclear Science Symposium - NSS'94.

On the Detection of Activation Patterns Using Principal Components Analysis

Iwao Kanno, Olaf B. Paulson, Stephen C. Strother, 1998 .

The Canadian Biomarker Integration Network in Depression (CAN-BIND): magnetic resonance imaging protocols

Stephen C. Strother, Stephen R. Arnott, Catherine Lebel, 2019, Journal of psychiatry & neuroscience : JPN.

Longitudinal cerebral blood flow changes during speech in hereditary ataxia

Stephen C. Strother, David A. Rottenberg, Christopher Gomez, 2010, Brain and Language.

Measuring Activation Pattern Reproducibility Using Resampling Techniques

Lars Kai Hansen, Stephen C. Strother, Kelly Rehm, 1998 .

Multivariate Predictive Relationship between Kinematic and Functional Activation Patterns in a PET Study of Visuomotor Learning

Stephen C. Strother, David A. Rottenberg, John J. Sidtis, 2000, NeuroImage.

The Stability of Behavioral PLS Results in Ill-Posed Neuroimaging Problems

Stephen C. Strother, Natasa Kovacevic, Anthony R. McIntosh, 2013 .

FDG PET Parkinson’s disease-related pattern as a biomarker for clinical trials in early stage disease

Stephen C. Strother, Miles N. Wernick, Nir Giladi, 2018, NeuroImage: Clinical.

Hippocampal tail volume as a predictive biomarker of antidepressant treatment outcomes in patients with major depressive disorder: a CAN-BIND report

Stephen C. Strother, Stephen R. Arnott, Glenda M. MacQueen, 2019, Neuropsychopharmacology.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Stephen C. Strother, Moyez Dharsee, Luciano Minuzzi, 2016, BMC Psychiatry.