Statistical Methods in Imaging Conference 2023 - Events Calendar - School of Public Health

May 22-24, 2023

The event will take place at the Graduate Hotel on the University of Minnesota Campus in Minneapolis.

SMI aims to bring together investigators from students to established researchers who are working on projects related to statistical methods and their applications in the broad area of imaging science, including, but not limited to, biomedical imaging, immunofluorescence imaging, and geospatial imaging.

View the conference schedule

Keynote Speakers and Founder's Talk

Our keynote speaker is Dr. Mingyao Li. Dr. Li received her PhD in Biostatistics from the University of Michigan in 2005. She was trained as a statistical geneticist, but since she joined the faculty at the University of Pennsylvania in 2006, she has gradually transitioned her research from traditional statistical genetics to statistical genomics with the goal of having a deeper understanding of the molecular mechanism of human disease. The central theme of her current research is to use statistical and machine learning methods to understand cellular heterogeneity in human-disease-relevant tissues, to characterize gene expression diversity across cell types, to study the patterns of cell state transition and crosstalk of various cells using data generated from single-cell and spatial transcriptomics studies, and to translate these findings into clinics. More recently, she expanded her expertise into computational pathology, which is critical when processing and analyzing spatial transcriptomics data. In addition to methods development, she is also interested in collaborating with researchers seeking to identify complex disease susceptibility genes and acting cell types. At UPenn, she serves as the Director of the Statistical Center for Single-Cell and Spatial Genomics. She also chairs the Graduate Program in Biostatistics. She is an elected member of the International Statistical Institute, a Fellow of the American Statistical Association, and a Fellow of the American Association for the Advancement of Science.

Title: Integrating spatial transcriptomics with histology to infer super-resolution tissue architecture

Abstract: The rapid development of spatial transcriptomics (ST) technologies has made it possible to measure gene expression within the original tissue contexts. The applications of ST have enabled researchers to characterize spatial gene expression patterns, study cell-cell communications, and resolve the spatiotemporal order of cellular development, which have transformed our understanding of the functional organization of tissues. Previous studies have shown that gene expression patterns are correlated with histological features, suggesting that gene expression can be predicted from histology images. However, these existing methods do not fully utilize the rich cellular information provided by high-resolution histology images. In this talk, I will present methods that we recently developed that aim to integrate gene expression with histology to computationally reconstruct ST data that cover the entire transcriptome with near-single-cell resolution. Through comprehensive analysis of diverse datasets generated from both diseased and normal tissues, we show that our super-resolution gene prediction is accurate and useful for different applications in tissue architecture inference.

Our second keynote speaker is Dr. Kelvin Lim, who is a Professor of Psychiatry, Director of Adult Mental Health Research, and Drs. T. J. and Ella M. Arneson Land-Grant Chair in Human Behavior at the University of Minnesota. Dr. Lim’s main research areas are in investigating how disruptions in brain connectivity influence pathophysiology, prognosis, and treatment of neuropsychiatric disorders.

Our Founder’s Talk will be given by Dr. Ranjan Maitra, who is a Professor in Statistics at Iowa State University. Dr. Maitra’s main research areas include the analysis of massive data, statistical computing, and statistical learning.

Tutorials

Introduction to the tidyverse and Quarto

Presented by: David Schneck

Tidyverse is a collection of open-source R packages designed with a similar philosophy and structure that aim to make data import, tidying, manipulation, and visualization straightforward and easily-reproducible. Tidyverse contains some of the most well-known and useful R packages for any application of data science, and is a must-have for any aspiring or veteran statistician or data scientist. The following packages will be explored in this workshop with time designated for hands-on coding examples:

dplyr: Data manipulation and pipes
ggplot2: data visualization and graphic creation
tidyr: tools to create clean and tidy working data
tibble: a re-imagining of the typical dataframe structure
stringr: tools for working with strings
Other packages that will be touched upon: readr, purrr, forcats

The second portion of this session will focus on the new technical publishing system: Quarto. Quarto builds upon the utility of Rmarkdown but adds several new features for utility, interactability, readability, and dissemination of analyses. Though Quarto can be used with other languages, we will focus on creating and exploring documents in R. Quarto is a cutting edge resource that will surely help in creating beautiful publications and other documents.

An Introduction to the ANTsX ecosystem through R

Presented by Dr. Nick Tustison and Dr. Brian Avants

The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. More recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and TensorFlow/Keras libraries (ANTsRNet). In this hands-on tutorial, we will showcase much of the available general and application-specific functionality in these R-based libraries which will permit the participant to create their own processing and analysis pipelines.

Poster Presentations

Poster abstract submission is open until Friday, April 21, 2023. Please submit poster abstracts using this Google Form.

Student Paper Competition

There will be two tracks for the student paper competition: 1) Theory and Methods, and 2) Case Studies and Applications. The selected winners for each track will be invited to present their papers in a session at the Statistical Methods in Imaging Conference held at the University of Minnesota on May 22-24, 2023. The first-place winner and runner-up for each track will also receive a cash prize of $1,000 and $500, respectively.

Eligibility
To be eligible for the student paper competition, the student must satisfy the following criteria:

i) Be a degree candidate at an accredited institution in any term during 2022 and 2023,
ii) Be the first author of the paper. The paper must not be published or accepted for publication at the time of submission,
iii) Be a current member of the Statistics in Imaging Section of the ASA;
iv) Be able to present the paper at SMI 2023.

Submission details
The deadline for submission to the student paper competition is April 3, 2023. Submissions should be sent to biostats@umn.edu with Subject Line either “SMI 2023: Theory and Methods” or “SMI 2023: Case Studies and Applications” depending on the intended track of the submission, and the email should contain the following four attachments in PDF format:

i) The applicant’s Curriculum Vitae;
ii) An unblinded version of the manuscript with no more than 26 pages, including the abstract, figures, tables and references. The manuscripts must be double-spaced with at least 11-point font size;
iii) A blinded version of the manuscript;
iv) A letter from a faculty member familiar with the student’s work. The faculty letter must include a verification of the applicant’s student status and, in the case of joint authorship, should indicate what is the contribution of the applicant to the paper.

Room Block Information

A room block from May 21 – May 25 is available at the Graduate Hotel – 615 Washington Ave SE, Minneapolis, MN 55414.

Prices start at $169 per night

Book your room

Participant Type	Cost
Faculty Attendee	$390
Student or Postdoc Attendee	$170

Questions? Contact Us

Mark Fiecas, mfiecas@umn.edu

Megan Schlick, adam0489@umn.edu

Conference Schedule

View additional details on the sessions below

Monday, 5/22

8:30 – 10 a.m.	Tutorial: Introduction to the tidyverse and Quarto Location: Pinnacle Ballroom
10 – 10:15 a.m.	Break
10:15 – 11:45 a.m.	Tutorial: An Introduction to the ANTsX ecosystem through R Location: Pinnacle Ballroom
11:45 a.m. – 1:10 p.m.	Lunch
1:10 – 2:40 p.m.	Student Paper Competition Winners Location: Pinnacle Ballroom
2:45 – 2:50 p.m.	Break
2:50 – 4:20 p.m.	New approaches to analyzing neuroimaging data Speakers: Meimei Liu, Jun Young Park, Kaizhou Lei, Zhengwu Zhang Location: Pathways	Collaborative Case Study: Novel application to neurological and neuropsychiatric diseases using different imaging techniques Speakers: Elizabeth Sweeney, Ceren Tozlu, Seonjoo Lee, Dana Tudorascu Location: Pinnacle Ballroom
4:20 – 6 p.m.	Poster Presentations / Mixer Location: Pinnacle Foyer and Pinnacle Ballroom

Tuesday, 5/23

8:30 – 10 a.m.	New Statistical Methods to Improve the Spatial-omics Analysis Pipeline Speakers: Gregory Hunt, Mansooreh Ahmadian, Zheng Li, and Lukas Weber Location: Pathways	Recent Developments on Brain Imaging Analysis Speakers: Kristin Linn, Zhaoxia Yu, Veera Baladandayuthapani, and Ruben Sanchez-Romero Location: Pinnacle Ballroom
10 – 10:10 a.m.	Break
10:10 – 11:10 a.m.	Keynote – Kelvin Lim Location: Pinnacle Ballroom
11:10 a.m. – 12:40 p.m.	Lunch
12:40 – 2:10 p.m.	Bayesian Methods Speakers: Dustin Pluta, Rajarshi Guhaniyogi, Michele Guindani, John Kornak Location: Pathways	Collaborative Case Study: Statistical Methods and Findings from Large Consortia Studies Speakers: Aaron Alexander-Bloch, Russell T. Shinohara, and Kaidi Kang Location: Pinnacle Ballroom
2:10 – 2:20 p.m.	Break
2:20 – 3:50 p.m.	Modern Statistical Methodology on Spatial, Neuroimaging, and Shape Data Analysis Speakers: Caitlin Ward, Yaotian Wang, Yuexuan Wu, and Shan Yu Location: Pathways	Recent advancements in statistical methods for brain connectome analysis Speakers: Ying Guo, Benjamin Risk, Yize Zhao, and Arkaprava Roy Location: Pinnacle Ballroom
3:50 – 4:00 p.m.	Break
4:00 – 5:30 p.m.	Efficient Modeling of Multi-Region High-Dimensional Molecular Data Speakers: Eric Lock, Xi Jiang, Souvik Seal and Weihua Guan Location: Pinnacle Ballroom	Recent Advances in Neuroimaging Statistics for Investigating Human Brain Function Speakers: Dayu Sun, Joshua Lukemire, Panpan Zhang, and Hyunnam Ryu Location: Pathways

Wednesday, 5/24

8:30 – 10 a.m.	Recent Advances in Spatial Analysis of Single-cell Imaging Speakers: Brooke L. Fridley, Siyuan Ma, Julia Wrobel and Misung Yi Location: Pathways	Statistical Methods for Brain Connectomes Speakers: Selena Wang, Yi Zhao, Rongjie Liu, and Xiao Xu Location: Pinnacle Ballroom
10 – 10:10 a.m.	Break
10:10 – 11:10 a.m.	Keynote – Mingyao Li Location: Pinnacle Ballroom
11:10 a.m. – 12:40 p.m.	Lunch
12:40 – 1:40 p.m.	Founder’s Talk – Rajan Maitra Location: Pinnacle Ballroom
1:40 – 1:50 p.m.	Break
1:50 – 3:20 p.m.	Statistical Methods for Analyzing Multiview and Multi-session Imaging Data Speakers: Suprateek Kundu, Vince Calhoun, and Xin Ma Location: Pathways	Collaborative Case Study: Event-related potential brain-computer interface data present challenges and opportunities for novel statistical methods Speakers: Jane E Huggins, Lexin Li, and Tianwen Ma Location: Pinnacle Ballroom
3:20 – 3:30 p.m.	Break
3:30 – 5:00 p.m.	Penalized Regression and Functional Data Analysis Speakers: Jeffrey Morris, Zhiling Gu, Todd Ogden and Gang Chen Location: Pinnacle Ballroom	Advances in Statistical Methods for Transmission Electron Microscopy Speakers: David S. Matteson, Andrew M. Thomas, and Yuchen Xu Location: Pathways
5:00 – 5:10 p.m.	Closing Remarks