ML-CDS 2021: Multimodal Learning and Fusion Across Scales for Clinical Decision Support


11:00-11:08 (UTC) Welcome notes

11:10-11:30 (UTC) Invited talk: "AI in Pediatric Oncology Imaging" by Professor Heike Daldrup-Link, Stanford University

11:30-12:15 (UTC) Session: Multimodal Segmentation and Registration

From Picoscale Pathology to Decascale Disease: Image Registration with a Scattering Transform and Varifolds for Manipulating Multiscale Data
Kaitlin M. Stouffer, Zhenzhen Wang, Eileen Xu, Karl Lee, Paige Lee, Michael I. Miller, and Daniel J. Tward

Merging and Annotating Teeth and Roots from Automated Segmentation of Multimodal Images
Romain Deleat-Besson, Celia Le, Winston Zhang, Najla Al Turkestani, Lucia Cevidanes, Jonas Bianchi, Antonio Ruellas, Marcela Gurgel, Camila Massaro, Aron Aliaga Del Castillo, Marcos Ioshida, Marilia Yatabe, Erika Benavides, Hector Rios, Fabiana Soki, Gisele Neiva, Kayvan Najarian, Jonathan Gryak, Martin Styner, Juan Fernando Aristizabal, Diego Rey, Maria Antonia Alvarez, Loris Bert, Reza Soroushmehr, and Juan Prieto

A Federated Multigraph Integration Approach for Connectional Brain Template Learning
Hizir Can Bayram, and Islem Rekik

12:15-12:20 (UTC) Break

12:20-13:05 (UTC) Session: Multimodal / Multiscale Disease Classification

Multi-Scale Hybrid Transformer Networks: Application to Prostate Disease Classification
Ainkaran Santhirasekaram, Karen Pinto, Mathias Winkler, Eric Aboagye, Ben Glocker, and Andrea Rockall

SAMA: Spatially-Aware Multimodal Network with Attention for Early Lung Cancer Diagnosis
Mafe Roa, Laura Daza, Maria Escobar, Angela Castillo, and Pablo Arbelaez

Feature Selection for Privileged Modalities in Disease Classification
Winston Zhang, Najla Al Turkestani, Jonas Bianchi, Celia Le, Romain Deleat-Besson, Antonio Ruellas, Lucia Cevidanes, Marilia Yatabe, Joao Goncalves, Erika Benavides, Fabiana Soki, Juan Prieto, Beatriz Paniaguam, Jonathan Gryak, Kayvan Najarian, Reza Soroushmehr

13:05-14:00 (UTC) Break

14:00-15:00 (UTC) Session: Multimodal Clinical Decision Support

Predicting Treatment Response in Prostate Cancer Patients Based on Multimodal PET/CT for Clinical Decision Support
Sobhan Moazemi, Markus Essler, Thomas Schultz, and Ralph A. Bundschuh

Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT
Pierre Fontaine, Vincent Andrearczyk, Valentin Oreiller, Joël Castelli, Mario Jreige, John O. Prior, and Adrien Depeursinge

Structure and Feature based Graph U-Net for Early Alzheimer's Disease Prediction
Yun Zhu, Xuegang Song, Yali Qiu, Chen Zhao, and Baiying Lei

A Method for Predicting Alzheimer's Disease based on the Fusion of Single Nucleotide Polymorphisms and Magnetic Resonance Feature Extraction
Yafeng Li, Yiyao Liu, Tianfu Wang, and Baiying Lei

15:00-15:30 (UTC) Panel Discussion

15:30-15:32 (UTC) Concluding remarks

Keynote Speaker

Italian Trulli

Heike Daldrup-Link, Professor of Radiology and of Pediatrics, Stanford University

Heike Elisabeth Daldrup-Link is a clinician-scientist in the Department of Radiology at Stanford University with subspecialisation in pediatric radiology, pediatric oncology imaging, and molecular imaging. Dr. Daldrup-Link trained at the University of Münster and the Technical University of Munich, Germany. She worked as an Assistant and Associate Professor at the University of California, San Francisco from 2003 to 2010, before joining Stanford Radiology in 2010. Her research interest focuses on the development of novel pediatric molecular imaging techniques, which interface observations of living cells with nanoparticle development and multimodality imaging technologies