Deploy Working Group

Expanding MONAI to cover the "end-to-end AI lifecycle"

Project MONAI was created with the goal of “accelerating the pace of research and development by providing a common software foundation and a vibrant community for medical imaging deep learning”.

There is a lot of research in the development and training of AI models by data science teams across the world, and the discipline is becoming mature thanks to initiatives like MONAI.

But in order to realize the value of all that effort and investments, the medical community has to naturally evolve to put all that new innovation seamlessly integrated within the different clinical workflows and systems, supporting and augmenting physicians, and freeing up their time to spend more time providing care to patients. That jump today is simply too high, almost a leap of blind faith. When we are talking about people’s lives, disease detection, diagnosis and treatment, not knowing how the results will affect care is simply unacceptable.

Therefore, we see an opportunity to create a set of intermediate steps, where researchers and physicians can build confidence in the techniques and approaches used with AI, deploy and connect with their research medical devices and systems in a controlled environment (i.e. Research PACS), and consume the results they need at the speed they are ready to, iterating over time until the overall AI inference infrastructure is ready to move to clinical environments, with a high certainty the transition will go smoothly.

We would love project MONAI to be the community where this idea develops, expanding its scope from AI from model training to QA evaluation first, and then to clinical deployments.

MONAI Deploy WG - scope diagram

Focus

The focus areas defined by the Deploy Strategy and Governance working group for 2021 are:

Define the journey from development and research to clinical environments in hospitals.
Implementation mindset. Create tangible assets: code and demos/prototypes. Start by defining an open AI deployment API.
Imaging first, then other modalities.
Interoperability with clinical systems. Starting with DICOM, then EHR.
Central repository to facilitate collaboration among institutions.

Deliverables

Assuming we have enough contributors to the Deploy Core working group, create:

By March 1st, first draft deployment roadmap.
By April 1st, final 2021 deployment roadmap.
By June 1st, open AI deployment API definition and first demo/prototype.

Members

Group Lead

David Bericat (NVIDIA) - [email protected]

Strategy and Governance Group members (~monthly 60 mins)

Ralf Floca (DKFZ) - [email protected]
Klaus Maier-Hein (DKFZ) - [email protected]
Klaus Kades (DKFZ) - [email protected]
Jonas Scherer (DKFZ) - [email protected]
Marco Nolden (DKFZ) - [email protected]
Daniel Rubin (Stanford) - [email protected]
Bennett Landman (Vanderbilt University/NSF) - [email protected]
Steve Langer (FlowSigma/NSF) - [email protected]
Brad Ericksonn (Mayo/FlowSigma) - [email protected]
Jayashree Kalpathy-Cramer (MGH) - [email protected]
Sharmila Majumdar (UCSF) - [email protected]
Anthony Costa (Mt. Sinai) - [email protected]
Haris Shuaib (Guy’s & St Thomas NHS Foundation Trust) - [email protected]
Krishna Juluru (NIH/MSKCC) - [email protected]
Jorge Cardoso (KCL) - [email protected]
Selnur Erdal (Mayo Jacksonville) [email protected]
Stephen Aylward (Kitware) [email protected]
Mona Flores (NVIDIA) - [email protected]
Risto Haukioja (NVIDIA) [email protected]
Rahul Choudhury (NVIDIA) [email protected]
Dana Groff (NVIDIA) [email protected]
Michael Zephyr (NVIDIA) [email protected]
Brad Genereaux (NVIDIA) [email protected]

Core WG members (~bi-weekly 90 mins)

Laurence Jackson (Guy’s & St Thomas NHS Foundation Trust) -[email protected]
Pouria Rouzrokh (Mayo) [email protected]
Karthik Ramadass (Vanderbilt) [email protected]
Yankai Huo (Vanderbilt) [email protected]
Kilian Hett (Vanderbilt) [email protected]

+Ralf Floca (DKFZ), Haris Shuaib (GSTT), Steve Langer (FlowSigma/NSF), Bennett Landman (Vanderbilt University/NSF), David Bericat (NVIDIA)