Radiological Society of North America (RSNA) Annual Meeting

Several ITCR investigators will be attending the Radiological Society of North America (RSNA) Annual Meeting in Chicago, December 1-6, 2019. Download the schedule for the presentations by ITCR investigators.

RSNA Annual Meeting, December 1-6, 2019

Link to the Meeting Program, search by session code.

Date/Time Session Name Session Code Session Location Associated ITCR Investigator Presentation Title
Every Day Exhibit IN022-EC-X  Learning Center Andrey Fedorov, Ron Kikinis 3D Slicer: A Community-Based Open Source Platform for Processing and 3D Visualization of DICOM Images
Every Day Exhibit BR144-ED-X Learning Center Despina Kontos A Primer on Machine Learning and Artificial Intelligence Applications in Breast Imaging
Every Day Exhibit  AI050 Learning Center Gordon Harris NCI Crowds Cure Cancer: Help Annotate Data from the Cancer Imaging Archive
Every Day Exhibit IN024-EC-X Learning Center Gordon Harris Interactive Web-Based Imaging Response Assessment Training Application for Cancer Clinical Trials
Every Day Exhibit GI226-ED-X Learning Center Hiro Yoshida Artificial intelligence (AI) for CT Colonography: The New Horizons of Colorectal Screening
Every Day Exhibit GI269-ED-X Learning Center Hiro Yoshida AI for Electronic Cleansing in Non-Cathartic CT Colonography 
Every Day Exhibit AI001-EC-X Learning Center Hiro Yoshida Virtual Reality of Self-Supervised Generative Adversarial Learning in Electronic Cleansing for CT Colonography

Sunday

12:30-1:00 PM Informatics Sunday Poster Discussions INS-SUA Learning Center Andrey Fedorov National Cancer Institute Imaging Data Commons
12:30-1:00 PM Artificial Intelligence Sunday Poster Discussions AIS-SUA Learning Center Daniel Rubin Optimizing Distributed Deep Learning Methods for Medical Image Data Heterogeneity Across Institutions
4:00-5:30 PM Creating Publicly Accessible Radiology Imaging Resources for Machine Learning and AI RCC13 E353C Jayashree Kalpathy-Cramer Creating Publicly Accessible Radiology Imaging Resources for Machine Learning and AI

Monday

7:15-8:15 AM Hot Topic Session: Radiomics in Thoracic Imaging SPSH20 E350 Hugo Aerts Deep Learning for Lung Screening
7:15-8:15 AM Hot Topic Session: Radiomics in Thoracic Imaging SPSH20 E350 Hugo Aerts Using AI-Radiomics for Cancer Charcterization
7:15-8:15 AM Hot Topic Session: Radiomics in Thoracic Imaging SPSH20 E350 Hugo Aerts AI-Based Radiomic Biomarkers at the Intersection of Oncology and Cardiology
8:30-12:00 PM Breast Series: MRI RC215 Arie Crown Theater Despina Kontos, Christos Davatzikos DCE-MRI Biomarkers of Changes in Peri-Tumoral and Intra-Tumoral Heterogeneity for Improving Early Prediction of Survival after Neoadjuvant Chemotherapy for Breast Cancer
8:30-12:00 PM Neuroradiology Series: AI in Neuroradiology RC205 S406B Jayashree Kalpathy-Cramer Brain Tumors and Other Lesions: How will AI Help?
8:30-12:00 PM Neuroradiology Series: AI in Neuroradiology RC205 S406B Jayashree Kalpathy-Cramer Hot Topic Panel: When is an AI Algorithm Ready for Clinical Practise?
10:30-12:00 PM Novel Discoveries Using the NCI's TCIA Public Data Sets RCC22 E353A Jayashree Kalpathy-Cramer Crowds Cure Cancer
10:30-12:00 PM Chest (Radiomics-Malignancy) SSC03 E451A Despina Kontos Impact of Interobserver Variability in Manual Segmentation of Non-Small Cell Lung Cancer (NSCLC) on Computed Tomography
10:30-12:00 PM Chest (Radiomics-Malignancy) SSC03 E451A Despina Kontos Correlation-Incorporated Hierarchical Clustering of High-Dimensional Radiomic Features for Prognostic Phenotype Identification of EGFR-Mutated Non-Small Cell Lung Cancer
3:00-4:00 PM Informatics (Artificial Intelligence: Triage, Screeing, Quality) SSE14 S406B Daniel Rubin Using Out of Distribution Detection to Fix Nearly All AI Models in Medical Imaging
3:00-4:00 PM Gastrointestinal (Artificial Intelligence and Machine Learning) SSE09 N230B Hiro Yoshida AI for Detecting Serrated Polyps in CT Colonography

Tuesday

8:30-12:00 PM Cardiac Series: Emerging Cardiovascular MR and CT Imaging RC303 E350 Hugo Aerts Deep Learning Quantification of Coronary Calcium on CT and Mortality in the National Lung Screening Trial (NLST)
10:30-12:00 PM Tuesday Morning Plenary Session PS31 E451B Anant Madabhushi Radio-Patho-Genomics: Computationally Integrating Disease Specific Features Across Scales
12:15-12:45 PM Informatics Tuesday Poster Discussions INS-TUA Learning Center Christos Davatzikos Interactively-Trained Segmentation Tool Leveraging Machine Learning and Geodesic Distance
12:15-12:45 PM Informatics Tuesday Poster Discussions INS-TUA Learning Center Gordon Harris Using the Open Health Imaging Foundation (OHIF) Framework to Build Web-Based Imaging Applications
12:15-12:45 PM Informatics Tuesday Poster Discussions INS-TUA Learning Center Daniel Rubin The Quantitative Image Feature Pipeline (QIFP): Automated Computation of Quantitative Image Features for Prediction of Clinical Characteristics (e.g., Malignancy, Response to Therapy, Overall Survival) in Subject Cohorts
3:00-4:00 PM Breast Imaging (Artificial Intelligence in Mammography) SSJ02 E451B Despina Kontos Deep-Learned Mammographic Phenotypes Indicate Racial Differences in Breast Parenchymal Patterns

Wednesday

8:30-10:00 AM Radiomics: Promise and Challenges RC525 S102CD Hugo Aerts  An Overview of Radiomics
8:30-10:00 AM Radiomics: Promise and Challenges RC525 S102CD Hugo Aerts  From Radiomics to Radiogenomics
8:30-10:00 AM Radiomics: Promise and Challenges RC525 S102CD Hugo Aerts  Challenges for Radiomics and Radiogenomics
8:30-10:00 AM Machine Learning for Radiotherapy Applications RC522 E352 Jayashree Kalpathy-Cramer Machine Learning Tumor Classification

Thursday

8:30-10:00 AM Radiomics: Informatics Tools and Databases RC625 E352 Jayashree Kalpathy-Cramer The Role of Challenges and Their Requirements
8:30-10:00 AM Radiomics: Informatics Tools and Databases RC625 E352 Andrey Fedorov Quantitative Image Analysis Tools: Communicating Quantitative Image Analysis Results
8:30-10:00 AM Tumor Imaging Metrics: Is it time to invest in a Service? RC618 S404AB Gordon Harris Should Every Radiology Department Invest in a Quantitative Imaging Lab?
10:30-12:00 PM Informatics (Education, Analytics, Quantitative) SSQ11 N229 Jayashree Kalpathy-Cramer How Not to Do Radiomics-Observations from a Double Baseline Study in Glioblastoma
12:15-12:45 PM Artificial Intelligence Thursday Poster Discussions AIS-THA Learning Center Daniel Rubin ePAD-AI: A Platform for Standards-Based Collaborative AI Application Development in Medical Imaging

Publish Date:  Monday, November 18, 2019