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NVIDIA at MICCAI 2022

Explore the best of MICCAI’s groundbreaking research in deep learning medical imaging research.

At the Medical Image Computing and Computer Assisted Intervention (MICCAI) conference at the Resorts World Convention Centre Singapore, NVIDIA experts shared the latest on MONAI, Federated Learning with NVIDIA Federated Learning Application Runtime Environment (NVFlare), and NVIDIA Clara Holoscan for a new era of software-defined medical devices.

MONAI and Holoscan Spotlight

Uniting Doctors with Data Scientists to Accelerate AI in Medicine

MONAI is uniting doctors with data scientists to accelerate AI in medicine. Hear from leaders and practitioners in medicine about how they are using MONAI to turn AI into clinical impact.

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Developing Digital Twins for Medical Devices

Watch how NVIDIA Clara Holoscan with NVIDIA Omniverse™ gives surgeons the ability to practice patient-specific procedures that can improve surgical efficiency and reduce patient time in the operating room.

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Open-Source Healthcare AI Innovation Continues to Expand with MONAI v1.0

Project MONAI is continuing to expand its capabilities to help developers accelerate medical imaging AI workflows. The release of MONAI 1.0 brings exciting updates, including MONAI Model Zoo, Auto-3D Segmentation, and active learning in MONAI Label.

Powering Ultra-High Speed Frame Rates in AI Medical Devices with the NVIDIA Clara Holoscan SDK

NVIDIA Clara Holoscan SDK now provides a lightning-fast frame rate of 240Hz for 4K video that allows developers to combine data from more sensors and build AI applications that can provide surgical guidance.

Workshops and Challenges

GRAIL: Graphs in biomedicAl Image Analysis
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SASHIMI: Simulation and Synthesis in Medical Imaging
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FAIR: aFfordable Healthcare and AI for Resource Diverse Global Health
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ACR-NCI-NVIDIA Breast Density Federated Learning Challenge
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Automated Machine Learning (AutoML) and Neural Architecture Search (NAS) in Medical Image Analysis
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DART: Domain Adaptation and Representation Transfer- Learning Transferable, Interpretable, and Robust Representations
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DeCaF: Distributed, Collaborative and Federated Learning
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Conference Schedule

At MICCAI 2021, explore a range of groundbreaking work in the field of medical imaging. Take a closer look at the scheduled NVIDIA sessions that are part of this year’s program.

PRE- CONFERENCE	MONDAY, 27TH SEPT	TUESDAY, 28TH SEPT	WEDNESDAY, 29TH SEPT	THURSDAY, 30TH SEPT	FRIDAY, 1ST OCT	POST- CONFERENCE
22nd - 24th Sept MONAI MICCAI Bootcamp 2021	Affordable healthcare and AI for Resource diverse global health (FAIR) All day	MICCAI Student Board: Academia & Industry event 19.30 pm UTC			Distributed And Collaborative Learning (DCL) All day	23rd - 24th Oct MICCAI Hackathon 9:00 AM UTC
	ASMUS – 2021: International Workshop of Advances in Simplifying Medical UltraSound (ASMUS) All day				Domain Adaptation and Representation Transfer (DART) All day
	Kick-Off MICCAI Hackathon 9:30 AM UTC

Featured Papers

Warm Start Active Learning with Proxy Labels & Selection via Semi-Supervised Fine-Tuning (PDF, 4,897 KB)
Vishwesh Nath, Holger Roth, Dong Yang, Daguang Xu

Efficient population based hyperparameter scheduling for medical image segmentation (PDF, 2,429 KB)
Yufan He, Dong Yang, Andriy Myronenko, Daguang Xu

Clinical-realistic Annotation for Histopathology Images with Probabilistic Semi-supervision: A Worst-case Study (PDF, 1,156 KB)
Ziyue Xu, Andriy Myronenko, Dong Yang, Holger Roth, Can Zhao, Xiaosong Wang, Daguang Xu

Ensembled Prediction of Rheumatic Heart Disease from Ungated Doppler Echocardiography Acquired in Low-Resource Settings
- Collaboration with Children’s National Hospital (PDF, 447 KB)
Pooneh Roshanitabrizi (CNHS), Holger Roth (NVIDIA), Alison Tompsett (CNHS), Athelia Paulli (CNHS), Kelsey Brown (CNHS), Andrea Beaton (CCHMC), Craig Sable (CNHS), Marius George Linguraru (CNHS)

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