Several ITCR investigators will be attending the Radiological Society of North America (RSNA) Annual Meeting in Chicago, November 25-30, 2018. Download the schedule for the presentations by ITCR investigators.
RSNA Annual Meeting, November 25-30, 2018
Link to the Meeting Program, search by session code.
| Date/Time | Session Name | Session Code | Session Location | ITCR Investigator | Presentation Title |
|---|---|---|---|---|---|
| Every Day | Meet the Experts | QRR001 | QIRR, Learning Center | Jayashree Kalpathy-Cramer, Bruce Rosen | DeepNeuro: Easy-To-Use and Validated Deep Learning Tools for Neuroimaging Analysis |
| Every Day | Meet the Experts | QRR003 | QIRR, Learning Center | Jayashree Kalpathy-Cramer, Andrey Fedorov, Ron Kikinis, Gordon Harris | DICOM4QI Demonstration and Connectathon: Structured Communication of Quantitative Image Analysis Results Using the DICOM Standard |
| Every Day | Meet the Experts | AI030 | AI Community, Learning Center | Jayashree Kalpathy-Cramer, Gordon Harris | Crowds Cure Cancer: Help Annotate Data from the Cancer Imaging Archive |
| Every Day | Meet the Experts | QRR002 | QIRR, Learning Center | Andrey Fedorov, Ron Kikinis | The 3D Slicer Open-Source Software Platform for Translational Research in Quantitative Imaging |
| Every Day | Meet the Experts | QRR020 | QIRR, Learning Center | Christos Davatzikos, Despina Kontos | Cancer Imaging Phenomics Toolkit (CaPTk): A Software Platform Leveraging Quantitative Radio(geno)mic Analytics for Computational Oncology |
| Every Day | Computer-Based Exhibit | AI022-EC-X | N/A | Hiro Yoshida | The Next Step in Electronic Cleansing for CT Colonography: Unsupervised Machine Learning |
| Every Day | Education Exhibit | GI302-ED-TUA12-ALL | Learning Center | Hiro Yoshida | Computer-Aided Detection (CADe) for CT Colonography: Benefits and Pitfalls |
Sunday |
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| 2:00-3:30 PM | Tumor Imaging Metrics: Is it Time to Invest in a Service? | RC118 | Room S504AB | Gordon Harris | Should Every Radiology Department Invest in a Quantitative Imaging Lab? |
Monday |
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| 8:30-12:00 PM | Neuroradiology Series: Brain Tumors | RC205 | Room S406B | Anant Madabhushi | Probabilistic Atlases of Pre-Treatment MRI Reveal Hemispheric and Lobe-Specific Spatial Distributions across Molecular Sub-Types of Diffuse Gliomas |
| 8:30-12:00 PM | Breast Series: Hot Topics | RC215 | Arie Crown Theater | Despina Kontos | Radiomic Phenotypes of Tumor Heterogeneity from Pre-Operative DCE-MRI Predict Breast Cancer Recurrence after 10-Year Follow-Up: Phenotype Discovery and Independent Validation |
| 8:30-12:00 PM | Breast Series: Hot Topics | RC215 | Arie Crown Theater | Anant Madabhushi | Novel Radiomic Descriptor of Tumor Vascular Morphology Identifies Responders to Neo-Adjuvant Chemotherapy on Pre-Treatment Breast MRI |
| 10:30-12:00 PM | Science Session with Keynote: Informatics (Artificial Intelligence in Radiology: Bleeding Edge) | SSC09 | Room E450A | Hugo Aerts | Non-invasive Tracking of Cancer Evolution using Deep Learning-Based Longitudinal Image Analysis |
| 12:15-12:45 PM | Breast Monday Poster Discussions | BRS-MOA | Learning Center | Despina Kontos | Volumetric versus Area-based Breast Density Assessment: Comparisons using Fully-Automated Quantitative Measurements in a Large Screening Population |
| 3:00-4:00 PM | Breast Imaging (Breast Density and Risk Assessment) | SSE01 | Room E451B | Despina Kontos | The Effect of Screening Modality and Race on BI-RADS Breast Density in a Large Urban Screening Cohort |
| 4:30-6:00 PM | Special Interest Session: Demystifying Machine Learning and Artificial Intelligence for the Radiologist | SPSI24 | Room E451A | Jayashree Kalpathy-Cramer | The Reality: Current Application of Machine Learning and Artificial Intelligence in Clinical Radiology and Research |
Tuesday |
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| 12:15-12:45 PM | Artificial Intelligence Tuesday Poster Discussions | AIS-TUA | Learning Center | Hugo Aerts | Transfer-Learning for Imaging-Based Lung Cancer Stratification |
Wednesday |
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| 8:30-10:00 AM | Deep Learning: Applying Machine Learning to Multi-disciplinary Precision Medicine Data Sets | RC553 | Room E451B | Joel Saltz, Hugo Aerts | Deep Learning: Applying Machine Learning to Multi-disciplinary Precision Medicine Data Sets |
| 8:30-12:00 PM | Neuroradiology Series: Stroke | RC505 | Room E450A | Jayashree Kalpathy-Cramer | Volumetric Segmentation of Acute Brain Infarcts on Diffusion-Weighted Imaging using Deep Learning |
| 3:00-4:00 PM | Science Session with Keynote: Breast Imaging (Risk-Based Screening: Should We Do It?) | SSM02 | Room E350 | Despina Kontos | The Effect of Screening Modality and Race on BI-RADS Breast Density in a Large Urban Screening Cohort |
| 3:00-4:00 PM | Cardiac (Arrhythmia and Electrophysiology) | SSM04 | Room S103AB | Anant Madabhushi | Radiographic Features of Pulmonary Veins Morphology from Chest CT Predicts Risk of Post-Ablation Atrial Fibrillation |
| 3:00-4:00 PM | Informatics (Quantitative Imaging) | SSM12 | Room E353B | Anant Madabhushi | Chaos-Based Fractal Radiomic Features of Nodule Vasculature Distinguish Granulomas from Adenocarcinomas on Non-Contrast Lung CT |
Thursday |
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| 10:30-12:00 PM | Novel Discoveries Using the NCI's Cancer Imaging Archive (TCIA) Public Data Sets | RCC52 | Room S501ABC | Jayashree Kalpathy-Cramer, Andrey Fedorov | Novel Discoveries Using the NCI's Cancer Imaging Archive (TCIA) Public Data Sets |
| 10:30-12:00 PM | Chest (Radiomics) | SSQ04 | Room E353A | Anant Madabhushi | Combination of Intra- and Peri-Tumoral Radiomic Features on Baseline CT are Prognostic of Recurrence and Overall Survival in Early Stage Non-Small Cell Lung Cancer (ES-NSCLC) Patients |
| 3:00-4:00 PM | Hot Topic Session: Biomarker and Personalized Medicine in Lung Cancer Imaging | SPSH52 | Room E350 | Hugo Aerts | Using Artificial Intelligence to Develop Non-invasive Biomarkers in Lung Cancer |
| 4:30-6:00 PM | Machine Learning for Radiotherapy Applications | RC722 | Room N227B | Jayashree Kalpathy-Cramer | Machine Learning Tumor Classification |
Publish Date: Tuesday, November 13, 2018