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8 !
Sun, 8/8/2021, 1:30 PM - 3:20 PM Virtual
Geometric Statistics for Complex Data — Invited Papers
Royal Statistical Society, International Indian Statistical Association, Section on Statistics in Imaging
Organizer(s): Karthik Bharath, University of Nottingham; Sebastian Kurtek, The Ohio State University
Chair(s): Sebastian Kurtek, The Ohio State University
1:35 PM Riemannian Structure on the Space of Measure Networks
Tom Needham, Florida State University; Samir Chowdhury, Stanford University
2:00 PM The Shape Space of Functional Data
Karthik Bharath, University of Nottingham; Ian H Jermyn, Durham University
2:25 PM Graph-Valued Models for Dimensionality Reduction and Regression
Aasa Feragen, Technical University of Denmark; Anna Calissano, Inria
2:50 PM Statistical shape analysis of elastic graphs Presentation
Aditi Basu Bal, Florida State University
3:15 PM Floor Discussion
 
 

26
Sun, 8/8/2021, 1:30 PM - 3:20 PM Virtual
Imaging Speed Session — Contributed Speed
Section on Statistics in Imaging
Chair(s): Dana L Tudorascu, University of Pittsburgh
1:35 PM A Regression Framework for Brain Network Distance Metrics
Chalmer E Tomlinson, UNC Chapel Hill; Paul J. Laurienti, Wake Forest School of Medicine; Robert G. Lyday, Wake Forest School of Medicine; Sean L. Simpson, Wake Forest School of Medicine
1:40 PM CoCoA: A Conditional Correlation Model with Association Size
Danni Tu, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania; Bridget Mahony, Section on Developmental Neurogenomics, National Institutes of Mental Health; Maxwell A. Bertolero, Department of Psychiatry, Perelman School of Medicine; Aaron F Alexander-Bloch, University of Pennsylvania; Danielle S. Bassett, Department of Bioengineering, University of Pennsylvania; Theodore D Satterthwaite, University of Pennsylvania; Armin Raznahan, Developmental Neurogenomics Unit, National Institute of Mental Health; Russell Shinohara, University of Pennsylvania
1:50 PM Fully Automated Detection of Paramagnetic Rims in Multiple Sclerosis Lesions on 3T Susceptibility-Based MR Imaging
Carolyn Lou, University of Pennsylvania; Pascal Sati, Cedars-Sinai Medical Center; Martina Absinta, National Institutes of Health; Kelly Clark, University of Pennsylvania; Jordan D Dworkin, Columbia University Medical Center; Alessandra M Valcarcel, Genentech, Inc.; Matthew K Schindler, University of Pennsylvania; Daniel S Reich, National Institutes of Health; Elizabeth M Sweeney, Weill Cornell Medicine; Russell Shinohara, University of Pennsylvania
1:55 PM WITHDRAWN: Statistical Characterization of the Generative Adversarial Network (GAN) Modeling of Seismic Data
Bradley C Wallet, Aramco Americas; Joseph McNease, University of Houston
2:00 PM A Study of Longitudinal Trends in Time-Frequency Transformations of EEG Data During a Learning Experiment
Joanna Boland, UCLA Department of Biostatistics; donatello telesca, UCLA; Catherine Sugar, UCLA Department of Biostatistics; Shafali Jeste, Department of Psychiatry and Biobehavioral Sciences; Cameron Goldbeck, UCLA Department of Biostatistics; Damla Senturk, UCLA
2:05 PM The Spike-and-Slab Elastic Net as a Classification Tool in Alzheimer's Disease
Justin Leach, University of Alabama at Birmingham; Lloyd Edwards, University of Alabama at Birmingham; Rajesh Kana, University of Alabama; Kristina Visscher, University of Alabama at Birmingham; Nengjun Yi, University of Alabama at Birmingham; Inmaculada Aban, University of Alabama at Birmingham
2:10 PM Investigating Latent Neurocircuitry Traits Underlying Brain Dynamic Functional Connectome
Jialu Ran, Emory University; Yikai Wang, Emory University; Ying Guo, Emory University
2:15 PM Estimation of Directional Parameters Under the Assumption of Continuity
ANJAN MANDAL, UNIVERSITY OF NEVADA LAS VEGAS
2:20 PM Clustering Brain Extreme Communities from Multi-Channel EEG Data
Matheus Bartolo Guerrero, KAUST; Raphaël Huser, KAUST; Hernando Ombao, King Abdullah University of Science and Technology
2:30 PM Clustering Using Probabilistic JIVE with Gaussian Mixtures
Ganzhong Tian, Emory University; John Hanfelt, Emory University; Raphiel Murden, Emory University; Deqiang Qiu, Emory University; Benjamin Risk, Emory University
2:35 PM Letting the LaxKAT Out of the Bag: A Powerful Kernel Test for Neuroimaging Studies Presentation
Jeremy Samuel Rubin, University of Pennsylvania; Simon N Vandekar, Vanderbilt University; Lior Rennert, Clemson University; Mackenzie Edmonson, University of Pennsylvania; Russell Shinohara, University of Pennsylvania
2:40 PM Bayesian Inferences on Spatially Varying Correlations via Gaussian Processes
Moyan Li, University of Michigan, Ann Arbor; Lexin Li, University of California, Berkeley; Jian Kang, University of Michigan
2:45 PM A New Correlation-Based Method for Co-Localization Analysis in Super-Resolution Images
Xueyan Liu, University of New Orleans; Clifford Guy, St. Jude Children's Research Hospital; Emilio Boada Romero, St. Jude Children's Research Hospital; Douglas Green, St. Jude Children's Research Hospital; Cheng Cheng, St. Jude Children’s Research Hospital; Hui Zhang, Division of Biostatistics, Northwestern University
2:50 PM Doubly Robust Targeted Minimum Loss-Based Estimation to Address Sampling Bias in Functional Connectivity Studies
Benjamin Risk, Emory University; Daniel Lidstone, Kennedy Krieger Institute; Liwei Wang, Emory University; David Benkeser, Emory University; Mary Beth Nebel, Johns Hopkins University School of Medicine
3:05 PM A Formal Bayesian Approach to SENSE Image Reconstruction Presentation
Chase Sakitis, Marquette University; Dan Rowe, Marquette University
3:15 PM Markov-Switching State-Space Models with Applications to Neuroimaging
David Degras, University of Massachusetts Boston; Hernando Ombao, King Abdullah University of Science and Technology; Chee Ming Ting, Monash University Malaysia
 
 

39 !
Sun, 8/8/2021, 3:30 PM - 5:20 PM Virtual
Recent Advances on Causal Inference and Mediation Analysis — Invited Papers
WNAR, Section on Statistics in Imaging, Section on Statistical Learning and Data Science
Organizer(s): Lexin Li, University of California, Berkeley
Chair(s): Qingyuan Zhao, University of Cambridge
3:35 PM Assumption-Lean Causal Inference for Direct and Indirect Effects
Stijn Vansteelandt, Ghent University; Oliver Hines, LSHTM
4:00 PM Testing Directed Acyclic Graph via Structural, Supervised, and Generative Adversarial Learning
Chengchun Shi, LSE; Yunzhe Zhou, University of California, Berkeley; Lexin Li, University of California, Berkeley
4:25 PM Causality in Cognitive Neuroscience: Leveraging Distributional Robustness
Sebastian Weichwald, University of Copenhagen; Jonas Peters, University of Copenhagen
4:50 PM Testing Mediation Effects Using Logic of Boolean Matrices
Lexin Li, University of California, Berkeley; Chengchun Shi, LSE
5:15 PM Floor Discussion
 
 

47 !
Sun, 8/8/2021, 3:30 PM - 5:20 PM Virtual
Geometric and Topological Information in Data Analysis — Topic-Contributed Papers
IMS, Section on Statistical Learning and Data Science, Section on Statistics in Imaging
Organizer(s): Hengrui Luo, Lawrence Berkeley National Laboratory
Chair(s): Chul Moon, Southern Methodist University
3:35 PM Characterizing Heterogenous Information in Persistent Homology with Applications to Molecular Structure Modeling
Zixuan Cang, University of California, Irvine; Guowei Wei, Michigan State Univesity
3:55 PM Gromov-Wasserstein Learning in a Riemannian Framework
Samir Chowdhury, Stanford University
4:15 PM Density Estimation and Modeling on Symmetric Spaces
Didong Li, Princeton University; Yulong Lu, University of Massachusetts Amherst; Emmanuel Chevallier, Aix Marseille University; David Dunson, Duke University
4:35 PM Convergence of Persistence Diagram in the Subcritical Regime
Takashi Owada, Purdue University, Department of Statistics
4:55 PM Combining Geometric and Topological Information for Boundary Estimation
Justin Strait, University of Georgia; Hengrui Luo, Lawrence Berkeley National Laboratory
Discussant: Hengrui Luo, Lawrence Berkeley National Laboratory
5:15 PM Floor Discussion
 
 

121 * !
Mon, 8/9/2021, 1:30 PM - 3:20 PM Virtual
In the Pipeline: Statistical Advances to Preserve Biological Signal in High-Throughput, Single-Cell Imaging and Sequencing Methods — Topic-Contributed Papers
Section on Statistics in Imaging, Section on Statistics in Genomics and Genetics, ENAR
Organizer(s): Coleman R Harris, Vanderbilt University Medical Center
Chair(s): Simon N Vandekar, Vanderbilt University
1:35 PM ComBat-Seq: Batch Effect Adjustment for RNA-Seq Count Data
W. Evan Johnson, Boston University School of Medicine; Yuqing Zhang, Gilead Sciences, Inc.; Giovanni Parmigiani, Harvard University
1:55 PM Comparison of Normalization Methods to Combine Batches of High-Dimensional Multiplexed Images Presentation
Coleman R Harris, Vanderbilt University Medical Center; Qi Liu, Vanderbilt University Medical Center; Eliot McKinley, Vanderbilt University Medical Center; Joseph Roland, Vanderbilt University Medical Center; Ken Lau, Vanderbilt University Medical Center; Robert Coffey, Vanderbilt University Medical Center; Simon N Vandekar, Vanderbilt University
2:15 PM Design and Analysis of High-Throughput Cell Imaging Studies
Johann Gagnon-Bartsch, University of Michigan; Gregory Hunt, College of William & Mary
2:35 PM Robust Re-Scaling of Imaging Data to Improve Discovery of Latent Effects
Gregory Hunt, College of William & Mary; Johann Gagnon-Bartsch, University of Michigan
2:55 PM Back to the Future: Viewing Single-Cell Assays Through the Lens of Chromatin Structure
Timothy J. Triche, Van Andel Institute; Benjamin K Johnson, Van Andel Institute; Hui J Shen, Van Andel Institute
3:15 PM Floor Discussion
 
 

151 * !
Tue, 8/10/2021, 10:00 AM - 11:50 AM Virtual
Recent Advances in Bayesian Approaches to Neuroimaging — Invited Papers
WNAR, Section on Statistics in Imaging, Section on Bayesian Statistical Science
Organizer(s): Aaron Wolfe Scheffler, University of California, San Francisco
Chair(s): Alec Chan-Golston, University of California, Merced
10:05 AM Quantifying Heterogeneity in Brain Imaging Data
donatello telesca, UCLA
10:30 AM A Bayesian Regression Framework for Brain Imaging Data with Multiple Structural- and Network-Valued Predictors
Aaron Wolfe Scheffler, University of California, San Francisco; Giovanni Battistella, Department of Neurology, University of California, San Francisco; Maria Luisa Mandelli, Department of Neurology, University of California, San Francisco; Maria Luisa Gorno-Tempini, Department of Neurology, University of California, San Francisco; Rajarshi Guhaniyogi, University of California, Santa Cruz
10:55 AM Sketching in Bayesian High Dimensional Regressions with Big Data
Rajarshi Guhaniyogi, University of California, Santa Cruz; Aaron Wolfe Scheffler, University of California, San Francisco
11:20 AM Recent Advances in Bayesian Approaches to Neuroimaging
Michele Guindani, University of California Irvine
11:45 AM Floor Discussion
 
 

155
Tue, 8/10/2021, 10:00 AM - 11:50 AM Virtual
Section on Statistics in Imaging Student Paper Award Winners — Topic-Contributed Papers
Section on Statistics in Imaging
Organizer(s): Simon N Vandekar, Vanderbilt University
Chair(s): Russell Shinohara, University of Pennsylvania
10:05 AM Sparse Bayesian Modeling of Hierarchical Independent Component Analysis: Reliable Estimation of Individual Differences in Brain Networks
Joshua Lukemire, Emory University; Ying Guo, Emory University
10:25 AM A Simple Permutation-Based Test of Intermodal Correspondence
Sarah M Weinstein, University of Pennsylvania; Simon N Vandekar, Vanderbilt University; Azeez Adebimpe, University of Pennsylvania; Tinashe M Tapera, University of Pennsylvania; Timothy Robert-Fitzgerald, University of Pennsylvania; Ruben C Gur, University of Pennsylvania; Raquel E Gur, University of Pennsylvania; Armin Raznahan, Developmental Neurogenomics Unit, National Institute of Mental Health; Theodore D Satterthwaite, University of Pennsylvania; Aaron F Alexander-Bloch, University of Pennsylvania; Russell Shinohara, University of Pennsylvania
10:45 AM Dynamic Gaussian Graphical Models to Study Time-Varying Clinical Symptom and Imaging Networks
Erin McDonnell, Columbia University; Shanghong Xie , Columbia Unviersity; Karen Marder, Columbia University; Yuanjia Wang, Columbia University
11:05 AM CatSIM: A Categorical Image Similarity Metric
Geoffrey Thompson, Indiana University; Ranjan Maitra, Iowa State University
11:25 AM A Multimodal, Multilevel Neuroimaging Model for Investigating Brain Connectome Development
Yingtian Hu, Department of Biostatistics and Bioinformatics, Emory University; Mahmoud Zeydabadinezhad, Department of Pediatrics, Emory University School of Medicine; Longchuan Li, Department of Pediatrics, Emory University School of Medicine; Ying Guo, Emory University
11:45 AM Floor Discussion
 
 

Register 178
Tue, 8/10/2021, 12:00 PM - 1:20 PM Virtual
Section on Statistics in Imaging P.M. Roundtable Discussion (Added Fee) — Roundtables PM Roundtable Discussion
Section on Statistics in Imaging
TL12: Discussing Scanners and Sites Variability in Neuroimaging Studies and Their Impact on Clinical and Methodological Grant Proposals
Dana L Tudorascu, University of Pittsburgh
 
 

204 * !
Tue, 8/10/2021, 1:30 PM - 3:20 PM Virtual
Bayesian Methods for the Analysis of Complex Brain Imaging Data — Topic-Contributed Papers
Section on Bayesian Statistical Science, International Society for Bayesian Analysis (ISBA), Section on Statistics in Imaging
Organizer(s): Francesco Denti, University of California, Irvine
Chair(s): Zhaoxia Yu, University of California, Irvine
1:35 PM A Hierarchical Bayesian Approach to Predicting Time-to-Conversion to Alzheimer's Disease Using a Longitudinal Map of Cortical Thickness
Mark Fiecas, University of Minnesota; Ning Dai, University of Minnesota; Hakmook Kang, Vanderbilt University; Galin Jones, University of Minnesota
1:55 PM Efficient Estimation of Brain Activation with Cortical Surface Data Using EM with a Bayesian General Linear Model Presentation
Daniel Spencer, Indiana University; Amanda Mejia, Indiana University
2:15 PM Detecting Brain Activation via Bayesian Mixture of Horseshoe Distributions
Francesco Denti, University of California, Irvine; Babak Shahbaba, University of California, Irvine; Michele Guindani, University of California Irvine; Ricardo Azevedo, University of California, Irvine; Sunil P. Gandhi, University of California, Irvine
2:35 PM Bayesian Non-Homogeneous Hidden Markov Models for Time-Varying Functional Connectivity
Jaylen Lee, University of California, Irvine; Michele Guindani, University of California Irvine; Marina Vannucci, Rice; Ryan Warnick, Rice University
2:55 PM Bayesian Nonparametric Analysis for the Detection of Spikes in Noisy Calcium Imaging Data
Laura D'Angelo, University of Padova; Michele Guindani, University of California Irvine; Antonio Canale, University of Padova; Zhaoxia Yu, University of California, Irvine
3:15 PM Floor Discussion
 
 

220772
Tue, 8/10/2021, 5:00 PM - 6:30 PM
Statistics in Imaging Open Business Meeting — Other Cmte/Business
Section on Statistics in Imaging
Chair(s): Tingting Zhang, University of Pittsburgh
Topic: Statistics in Imaging Open Business Meeting
Time: Aug 10, 2021 05:00 PM Eastern Time (US and Canada)


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219 * !
Wed, 8/11/2021, 10:00 AM - 11:50 AM Virtual
Artificial Intelligence and Machine Learning in Medical Imaging for Drug Development — Invited Papers
Section on Statistics in Imaging, Section on Medical Devices and Diagnostics, Biopharmaceutical Section
Organizer(s): Bushi Wang, Boehringer Ingelheim Pharmaceuticals Inc.
Chair(s): Sue-Jane Wang, FDA
10:05 AM Using Deep Learning on HRCT Scan to Predict Pulmonary Fibrosis Progression and Support Early Clinical Development Decision
Bushi Wang, Boehringer Ingelheim Pharmaceuticals Inc.; Yi Liu, Boehringer Ingelheim; Hao Li, Boeringer-Ingelheim
10:25 AM Application of Machine Learning in Medical Imaging: Overview of Novartis Radiomics Projects
Thibaud Coroller, Novartis
10:45 AM Histopathology and AI for Cancer Subtype and Mutation Detection
Narges Razavian, New York University Langone Health
11:05 AM Development and Clinical Evaluation of Quantitative Lung Fibrosis Scores on CT Images in Clinical Trials: Idiopathic Pulmonary Fibrosis and Scleroderma Lung Disease
Grace Hyun Kim, UCLA; Jonathan Goldin, UCLA; Matthew Brown, UCLA
11:25 AM Recent Advances in Machine Learning in Medical Image Analysis
Fei Wang, Weill Cornell Medicine
11:45 AM Floor Discussion
 
 

334 * !
Thu, 8/12/2021, 10:00 AM - 11:50 AM Virtual
Functional and Geometric Approaches for Imaging Data — Invited Papers
Section on Statistics in Imaging, ENAR, Biometrics Section
Organizer(s): Shariq Mohammed, University of Michigan
Chair(s): Veerabhadran Baladandayuthapani, University of Michigan
10:05 AM Machine Learning Frameworks for Association Mapping with 3D Shapes and High-Resolution Imaging
Lorin Crawford, Microsoft Research
10:30 AM Tumor Radiogenomics with Bayesian Layered Variable Selection
Shariq Mohammed, University of Michigan; Sebastian Kurtek, The Ohio State University; Karthik Bharath, University of Nottingham; Arvind Rao, University of Michigan; Veerabhadran Baladandayuthapani, University of Michigan
10:55 AM Simultaneous Registration and Estimation of Fractional Anisotropy Profiles from Fragmented and Noisy Observations
Sebastian Kurtek, The Ohio State University; James Matuk, Department of Statistics, The Ohio State University; Oksana Chkrebtii, The Ohio State University; Karthik Bharath, University of Nottingham
11:20 AM Learning Temporal Evolution of Spatial Dependence with Non-separable, Non-stationary Gaussian Process Models
Shiwei Lan, Arizona State University
11:45 AM Floor Discussion