Orals

3D Infant Pose Estimation Using Transfer Learning
Simon Ellershaw (Imperial College London)*; Luca Schmidtke (Imperial College London); Nidal Khatib (Imperial College London); Jonathan Eden (Imperial College London); Anna Jones ( Guy's and St Thomas' NHS Foundation Trust); Sofia Dall'Orso (Imperial College London); Silvia Muceli (Chalmers University of Technology); Etienne Burdet (Imperial College London); Niamh Nowlan (Imperial College London); Tomoki Arichi (King's College London); Bernhard Kainz (Imperial College London)

Brain2Word: Improving Brain Decoding Methods and Evaluation
Nicolas Affolter (ETHZ); Beni Egressy (ETH Zurich); Damian Pascual (ETHZ)*; Roger Wattenhofer (ETH Zurich)

Context-aware Self-supervised Learning for Medical Images Using Graph Neural Network
Li Sun (University of Pittsburgh)*; Ke Yu (University of Pittsburgh); Kayhan Batmanghelich (University of Pittsburgh)

Deep learning to assist radiologists in breast cancer diagnosis with ultrasound imaging
Yiqiu Shen (New York University); Farah E Shamout (New York University)*; Jamie Oliver (NYU Langone Health); Kawshik Kannan (New York University); Jungkyu Park (New York University); Nan Wu (New York University); Connor Huddleston (NYU Langone Health); Alexandra Millet (NYU Langone Health); Cathy Tyma (NYU Langone Health); Cindy Leonard (NYU Langone Health); Cindy Lee (NYU Langone Health); Chloe Chhor (NYU Langone Health); Christopher Moczulski (NYU Langone Health); Divya Awal (NYU Langone Health); Jaime Altabet (NYU Langone Health); Naziya Samreen (NYU Langone Health); Reyhan Mohammed (NYU Langone Health); Robin Ehrenpreis (NYU Langone Health); Sheila Kumari-Subaiya (NYU Langone Health); Stacey Gandhi (NYU Langone Health); Stacey Wolfson (New York University); Yiming Gao (New York University); Alana Lewin (New York University); Beatriu Reig (New York University); Linda Moy (New York University); Laura Heacock (New York University ); Krzysztof Geras (NYU)

DeepSim: Semantic similarity metrics for learned image registration
Steffen Czolbe (University of Copenhagen)*; Aasa Feragen (Technical University of Denmark); Oswin Krause (University of Copenhagen)

Privacy-preserving medical image analysis
Alexander Ziller (Technische Universität München)*; Jonathan Passerat-Palmbach (Imperial College London / ConsenSys); Théo Ryffel (INRIA); Dmitrii Usynin (Imperial College London); Andrew Trask (OpenMined; University of Oxford); Ionésio Da Lima Costa Junior (Universidade Federal de Campina Grande); Jason Mancuso (Dropout Labs); Marcus Makowski (Technische Universität München); Daniel Rueckert (Technische Universität München); Rickmer Braren (Technische Universität München); Georgios Kaissis (Technische Universität München)

Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks
Darya Trofimova (DKFZ)*

Using StyleGAN for Visual Interpretability of Deep Learning Models on Medical Images
Kathryn Schutte (Owkin)*; Olivier Moindrot (Owkin); Paul Herent (Owkin); Jean-Baptiste Schiratti (Owkin); Simon Jegou (Owkin)

Posters

3D UNet with GAN Discriminator for Robust Localisation of the Fetal Brain and Trunk in MRI with Partial Coverage of the Fetal Body
Alena Uus (KING'S COLLEGE LONDON)*; Irina Grigorescu (King's College London); Milou Van Poppel (King's College London); Emer Hughes (King's College London); Johannes Steinweg (King's College London); Thomas Roberts (King's College London); David Lloyd (King's College London); Kuberan Pushparajah (King's College London); Maria Deprez (King's College London)

A Bayesian Unsupervised Deep-Learning Based Approach for Deformable Image Registration
Samah Khawaled (Technion)*; Moti Freiman (Technion - Israel Institute of Technology)

A Critic Evaluation Of Covid-19 Automatic Detection From X-Ray Images
Gianluca Maguolo (University of Padova)*; Loris Nanni (university of Padova)

A Deep Learning Model to Detect Anemia from Echocardiography
John W Hughes (Stanford University)*; James Zou (Stanford University); David Ouyang (Cedars-Sinai Medical Center)

Adversarial Cycle-consistent Synthesis of Cerebral Microbleeds for Data Augmentation
Khrystyna Faryna (Radboud University Medical Center )*; Kevin Koschmieder (Radboud University Medical Center); Bram van Ginneken (Radboud University Medical Center)

AI System for Predicting the Deterioration of COVID-19 Patients in the Emergency Department
Farah E Shamout (New York University)*; Yiqiu Shen (New York University); Nan Wu (New York University); Aakash Kaku (NYU Center for Data Science); Jungkyu Park (New York University); Taro Makino (NYU); Stanislaw Jastrzebski (New York University); Duo Wang (NYU Langone Health); Ben Zhang (NYU Langone Health); Siddhant Dogra (NYU Langone Health); Meng Cao (NYU Langone Health); Narges Razavian (New York University School of Medicine); David Kudlowitz (NYU Langone Health); Lea Azour (NYU Grossman School of Medicine); William Moore (NYU Langone Health); Yvonne Lui (New York University School of Medicine); Yindalon Aphinyanaphongs (New York University School of Medicine); Carlos Fernandez-Granda (NYU); Krzysztof J Geras (New York University)

Annotation-Efficient Deep Semi-Supervised Learning for Automatic Knee Osteoarthritis Severity Diagnosis from Plain Radiographs
Huy Hoang Nguyen (University of Oulu)*; Simo Saarakkala (University of Oulu, Finland); Matthew Blaschko (KU Leuven); Aleksei Tiulpin (University of Oulu)

Attention Transfer Outperforms Transfer Learning in Medical Image Disease Classifiers
Sina Akbarian (University of Toronto)*; Laleh Seyyed-Kalantari (University of Toronto, Vector Institute); Farzad Khalvati (University of Toronto); Elham Dolatabadi (Vector Institute; University of Toronto)

Autoencoder Image Compression Algorithm for Reduction of Resource Requirements
Young Joon Kwon (Icahn School of Medicine at Mount Sinai)*; Danielle Toussie (Icahn School of Medicine at Mount Sinai); G Anthony Reina (Intel Corporation); Ping Tak Peter Tang (Facebook Research); Amish Doshi (Icahn School of Medicine at Mount Sinai); Eric Oermann (NYU Grossman School of Medicine); Anthony Costa (Icahn School of Medicine at Mount Sinai)

Biomechanical Modelling of Brain Atrophy through Deep Learning
Mariana da Silva (King's College London)*; Kara Garcia (Indiana University ); Carole Sudre (King's College London); Cher Bass (King's College London); Jorge Cardoso (Kings College London); Emma C Robinson (King's College)

Can We Learn to Explain Chest X-Rays?: A Cardiomegaly Use Case
Neil Jethani (NYU)*; Mukund Sudarshan (New York University); Lea Azour (NYU Grossman School of Medicine); William Moore (NYU); Yindalon Aphinyanaphongs (New York University School of Medicine); Rajesh Ranganath (New York University)

Classification with a Domain Shift in Medical Imaging
Alessandro Fontanella (University of Edinburgh)*; Emma J R Pead (The University of Edinburgh); Tom J MacGillivray (University of Edinburgh); Miguel Bernabeu (University of Edinburgh); Amos Storkey (U Edinburgh)

Clinical Validation of Machine Learning Algorithm Generated Images
Young Joon Kwon (Icahn School of Medicine at Mount Sinai)*; Danielle Toussie (Icahn School of Medicine at Mount Sinai); Lea Azour (NYU Grossman School of Medicine); Jose Concepcion (Icahn School of Medicine at Mount Sinai); Corey Eber (Icahn School of Medicine at Mount Sinai); G Anthony Reina (Intel Corporation); Ping Tak Peter Tang (Facebook Research); Amish Doshi (Icahn School of Medicine at Mount Sinai); Eric Oermann (NYU Grossman School of Medicine); Anthony Costa (Icahn School of Medicine at Mount Sinai)

Community Detection in Medical Image Datasets: Using Wavelets and Spectral Clustering
Roozbeh Yousefzadeh (Yale University)*

Comparing Sparse and Deep Neural Network(NN)s: Using AI to Detect Cancer
Charles M. S. Strauss (New Mexico Consortium)*; Austin Thresher (New Mexico Consortium); Garrett Kenyon (Los Alamos National Laboratory)

COVIDNet-S: SARS-CoV-2 Lung Disease Severity Grading of Chest X-rays using Deep Convolutional Neural Networks
Alexander Wong (University of Waterloo)*; Zhong Qiu Lin (University of Waterloo); Linda Wang (University of Waterloo); Audrey Chung (University of Waterloo); Timothy Duong (Montefiore Medical Center and Albert Einstein College of Medicine); Beiyi Shen (Stony Brook Medicine); Almas Abbasi (Stony Brook Medicine); Mahsa Hoshmand-Kochi (Stony Brook Medicine)

Decoding Brain States: Clustering fMRI Dynamic Functional Connectivity Timeseries with Deep Autoencoders
Arthur P Spencer (University of Bristol)*; Marc Goodfellow (University of Exeter)

Deep Learning Extracts Novel MRI Biomarkers for Alzheimer’s Disease Progression
Yi Li (JAX)*

Diffusion MRI-based Structural Connectivity Robustly Rredicts "brain-age''
Guruprasath gurusamy (Indian Institute of Science)*; Varsha Sreenivasan (Indian Institute of Science); Devarajan Sridharan (Indian Institute of Science); Naren Rao (Indian Institute of Science)

Embracing the Disharmony in Heterogeneous Medical Data
Rongguang Wang (University of Pennsylvania)*; Pratik Chaudhari (University of Pennsylvania); Christos Davatzikos (University of Pennsylvania)

Encoding Clinical Priori in 3D Convolutional Neural Networks for Prostate Cancer Detection in bpMRI
Anindo Saha (Radboud University Medical Center)*; Matin Hosseinzadeh (Radboud University Medical Center); Henkjan Huisman (Radboudumc)

Harmonization and the Worst Scanner Syndrome
Daniel C Moyer (Massachusetts Institute of Technology)*; Polina Golland (MIT)

Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN
Li Sun (University of Pittsburgh)*; Junxiang Chen (University of Pittsburgh); Yanwu Xu (University of Pittsburgh); Mingming Gong (University of Melbourne); Ke Yu (University of Pittsburgh); Kayhan Batmanghelich (University of Pittsburgh)

Hip Fracture Risk Modeling Using DXA and Deep Learning
Yannik Glaser (University of Hawaii at Manoa); Peter Sadowski (University of Hawaii at Manoa)*; Thomas Wolfgruber (University of Hawaii at Manoa); Lily Lui (California Pacific Medical Center); Steven Cummings (California Pacific Medical Center); John Shepherd (University of Hawaii at Manoa)

Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training
Andrei Margeloiu (University of Cambridge)*; Nikola Simidjievski (University of Cambridge ); Mateja Jamnik (University of Cambridge); Adrian Weller (University of Cambridge)

Joint Hierarchical Bayesian Learning of Full-structure Noise for Brain Source Imaging
Ali Hashemi (Technische Universität Berlin)*; Chang Cai (University of California, San Francisco); Klaus-Robert Müller (Technische Universität Berlin); Srikantan Nagarajan (UCSF); Stefan Haufe (Charité – Universitätsmedizin Berlin)

Learning MRI Contrast Agnostic Registration
Malte Hoffmann (Harvard Medical School)*; Benjamin Billot (UCL); Juan Eugenio Iglesias (UCL); Bruce Fischl (Massachusetts General Hospital / Harvard Medical School); Adrian V Dalca (MIT)

Learning to Estimate a Surrogate Respiratory Signal from Cardiac Motion by Signal-to-signal Translation
Akshay B Iyer (Radiology Dept, UMass Medical School)*; Clifford Lindsay (UMass Medical School); Hendrik Pretorius (Radiology Dept, UMass Medical School); Michael King (Radiology Dept, UMass Medical School)

LVHNet: Detecting Cardiac Structural Abnormalities with Chest X-Rays
Shreyas Bhave (Columbia University)*; Pierre Elias (Columbia University Medical Center ); Victor Rodriguez (Columbia University); Timothy Poterucha (Columbia University Medical Center); Simi Mutasa (Columbia University Medical Center); Jay Le b (Columbia University Medical Center); Nir Uriel (Columbia University Medical Center); Adler Perotte (Columbia University)

Modified VGG16 Network for Medical Image Analysis
Amulya Vatsavai (RCHS)*; FN-Anonymous1 LN-Anonymous1 (NCSU)

Multi-Label Incremental Few-Shot Learning for Medical Image Pathology classifiers
Laleh Seyyed-Kalantari (University of Toronto, Vector Institute)*; Karsten Roth (Heidelberg University, Mila); Mengye Ren (Uber ATG, University of Toronto); Parsa Torabian (University of Waterloo); Joseph Paul Cohen (Mila, University of Montreal); Marzyeh Ghassemi (University of Toronto, Vector Institute)

MVD-Fuse: Detection of White Matter Degeneration via Multi-View Learning of Diffusion Microstructure
Shreyas Fadnavis (Indiana University Bloomington)*; Pablo Polosecki (IBM Research); Eleftherios Garyfallidis (Indiana University); Eduardo Castro (IBM Research); Guillermo Cecchi (IBM)

Predicting the Need for Intensive Care for COVID-19 Patients using Deep Learning on Chest Radiography
Qiyuan Hu (University of Chicago)*; Karen Drukker (University of Chicago); Maryellen Giger (University of Chicago)

Probabilistic Recovery of Missing Phase Images in Contrast-Enhanced CT
Dhruv V Patel (University of Southern California)*; Chiao-Chih Hsu (University of Southern California); Bino Varghese (University of Southern California); Steven Cen (University of Southern California); Darryl Hwang (University of Southern California); Inderbir Singh Gill (University of Southern California); Vinay Duddalwar (University of Southern California); Assad Oberai (University of Southern California)

Quantification of Task Similarity for Efficient Knowledge Transfer in Biomedical Image Analysis
Patrick Scholz ( German Cancer Research Center)*; Lena Maier-Hein ("German Cancer Research Center, Germany")

RANDGAN: Randomized Generative Adversarial Network for Detection of COVID-19 in Chest X-ray
Saman Motamed (University of Toronto)*; Farzad Khalvati (University of Toronto); Patrik Rogalla (University of Toronto)

RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
Benjamin Hou (Imperial College London)*; Georgios Kaissis (Technische Universität München); Ronald Summers (NIH); Bernhard Kainz (Imperial College London)

Retrospective Motion Correction of MR Images using Prior-Assisted Deep Learning
Soumick Chatterjee (Otto von Guericke University Magdeburg)*; Alessandro Sciarra (MedDigit, OVGU, Magdeburg); Max Dünnwald (Otto von Guericke University Magdeburg); Steffen Oeltze-Jafra ("Dept. of Neurology, Otto-v.-Guericke Univ. Magdeburg"); Andreas Nurnberger ( Magdeburg University); Oliver Speck (Otto von Guericke University Magdeburg)

Scalable Solutions for MR Image Classification of Alzheimer's Disease [poster]
Sarah Catharina Brueningk (ETH Zurich)*; Felix Hensel (ETH Zurich); Catherine Jutzeler (ETH Zurich); Bastian A Rieck (MLCB, D-BSSE, ETH Zurich)

Self-supervised Out-of-distribution Detection in Brain CT Scans
Abinav Ravi (TUM); Seong Tae Kim (Technical University of Munich)*; Rami Eisawy (deepc); Franz Pfister (deepc); Nassir Navab (Technische Universität München, Germany)

Semantic Video Segmentation for Intracytoplasmic Sperm Injection Procedures
Peter He (Imperial College London)*; Raksha Jain (Imperial College London); Jérôme Chambost (Apricity); Céline Jacques (Apricity); Cristina Hickman (Imperial College London)

Semi-Supervised Learning of MR Image Synthesis without Fully-Sampled Ground-Truth Acquisitions
Mahmut Yurt (Bilkent University)*; Berk Tinaz (University of Southern California); Salman Ul Hassan Dar (Bilkent University); Muzaffer Özbey (Bilkent University); Tolga Cukur (Bilkent University)

StND: Streamline-based Non-rigid partial-Deformation Tractography Registration
Bramsh Q Chandio (INDIANA UNIVERSITY)*; Eleftherios Garyfallidis (Indiana University)

Towards Disease-aware Image Editing of Chest X-rays
Aakash saboo (CARING Research)*; Sai Niranjan Ramachandran (Indian Institute Of Science); Kai Dierkes (Pupil Labs Research); Hacer Yalim Keles (Ankara University)

Ultrasound Diagnosis of COVID-19: Robustness and Explainability
Jay Roberts (MIT Lincoln Laboratory)*; Theodoros Tsiligkaridis (MIT Lincoln Laboratory)

Unsupervised Detection of Hypoplastic Left Heart Syndrome in Fetal Screening
Elisa Chotzoglou (Imperial College London)*; Samuel Budd (Imperial College London); Thomas Day (King's College London); John Simpson (Evelina London Children's Hospital); Bernhard Kainz (Imperial College London)

Zero-dose PET Reconstruction with Missing Input by U-Net with Attention Modules
Jiahong Ouyang (Stanford University)*; Kevin Chen (Stanford University); Greg Zaharchuk (Stanford University)